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Publisher: Springer-Verlag (Total: 2352 journals)

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Showing 1 - 200 of 2352 Journals sorted alphabetically
3D Research     Hybrid Journal   (Followers: 18, SJR: 0.214, h-index: 10)
4OR: A Quarterly J. of Operations Research     Hybrid Journal   (Followers: 9, SJR: 1.073, h-index: 25)
AAPS J.     Hybrid Journal   (Followers: 20, SJR: 1.192, h-index: 74)
AAPS PharmSciTech     Hybrid Journal   (Followers: 6, SJR: 0.718, h-index: 54)
Abdominal Imaging     Hybrid Journal   (Followers: 14, SJR: 0.723, h-index: 60)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 3, SJR: 0.447, h-index: 12)
Academic Psychiatry     Full-text available via subscription   (Followers: 22, SJR: 0.492, h-index: 32)
Academic Questions     Hybrid Journal   (Followers: 7, SJR: 0.135, h-index: 6)
Accreditation and Quality Assurance: J. for Quality, Comparability and Reliability in Chemical Measurement     Hybrid Journal   (Followers: 26, SJR: 0.378, h-index: 30)
Acoustical Physics     Hybrid Journal   (Followers: 11, SJR: 0.355, h-index: 20)
Acoustics Australia     Hybrid Journal  
Acta Analytica     Hybrid Journal   (Followers: 7, SJR: 0.387, h-index: 6)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1, SJR: 0.624, h-index: 34)
Acta Biotheoretica     Hybrid Journal   (Followers: 5, SJR: 0.419, h-index: 25)
Acta Diabetologica     Hybrid Journal   (Followers: 14, SJR: 1.318, h-index: 46)
Acta Endoscopica     Hybrid Journal   (Followers: 1, SJR: 0.113, h-index: 8)
acta ethologica     Hybrid Journal   (Followers: 4, SJR: 0.465, h-index: 23)
Acta Geochimica     Hybrid Journal   (Followers: 5)
Acta Geodaetica et Geophysica     Hybrid Journal   (Followers: 1, SJR: 0.294, h-index: 13)
Acta Geotechnica     Hybrid Journal   (Followers: 7, SJR: 1.818, h-index: 22)
Acta Informatica     Hybrid Journal   (Followers: 5, SJR: 0.524, h-index: 32)
Acta Mathematica     Hybrid Journal   (Followers: 11, SJR: 8.021, h-index: 47)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2, SJR: 0.53, h-index: 29)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 5, SJR: 0.406, h-index: 30)
Acta Mathematica Vietnamica     Hybrid Journal   (SJR: 0.451, h-index: 5)
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal   (SJR: 0.22, h-index: 20)
Acta Mechanica     Hybrid Journal   (Followers: 20, SJR: 0.898, h-index: 52)
Acta Mechanica Sinica     Hybrid Journal   (Followers: 5, SJR: 0.426, h-index: 29)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5, SJR: 0.525, h-index: 18)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.524, h-index: 14)
Acta Neurochirurgica     Hybrid Journal   (Followers: 6, SJR: 0.833, h-index: 73)
Acta Neurologica Belgica     Hybrid Journal   (SJR: 0.348, h-index: 27)
Acta Neuropathologica     Hybrid Journal   (Followers: 5, SJR: 6.61, h-index: 117)
Acta Oceanologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.295, h-index: 17)
Acta Parasitologica     Hybrid Journal   (Followers: 9, SJR: 0.581, h-index: 28)
Acta Physiologiae Plantarum     Hybrid Journal   (Followers: 2, SJR: 0.551, h-index: 39)
Acta Politica     Hybrid Journal   (Followers: 13, SJR: 0.658, h-index: 20)
Activitas Nervosa Superior     Hybrid Journal  
adhäsion KLEBEN & DICHTEN     Hybrid Journal   (Followers: 5, SJR: 0.103, h-index: 4)
ADHD Attention Deficit and Hyperactivity Disorders     Hybrid Journal   (Followers: 23, SJR: 0.871, h-index: 15)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 8)
Administration and Policy in Mental Health and Mental Health Services Research     Partially Free   (Followers: 15, SJR: 0.795, h-index: 40)
Adsorption     Hybrid Journal   (Followers: 4, SJR: 0.774, h-index: 52)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 3, SJR: 0.319, h-index: 15)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 34, SJR: 0.959, h-index: 44)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15, SJR: 1.255, h-index: 44)
Advances in Contraception     Hybrid Journal   (Followers: 3)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52, SJR: 1.113, h-index: 14)
Advances in Gerontology     Partially Free   (Followers: 9, SJR: 0.141, h-index: 3)
Advances in Health Sciences Education     Hybrid Journal   (Followers: 22, SJR: 1.397, h-index: 42)
Advances in Manufacturing     Hybrid Journal   (Followers: 3, SJR: 0.2, h-index: 4)
Advances in Polymer Science     Hybrid Journal   (Followers: 41, SJR: 0.637, h-index: 89)
Advances in Therapy     Hybrid Journal   (Followers: 5, SJR: 0.79, h-index: 44)
Aegean Review of the Law of the Sea and Maritime Law     Hybrid Journal   (Followers: 7)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2, SJR: 0.882, h-index: 23)
Aerobiologia     Hybrid Journal   (Followers: 1, SJR: 0.511, h-index: 36)
Aesthetic Plastic Surgery     Hybrid Journal   (Followers: 9, SJR: 0.821, h-index: 49)
African Archaeological Review     Hybrid Journal   (Followers: 15, SJR: 0.612, h-index: 24)
Afrika Matematika     Hybrid Journal   (Followers: 1, SJR: 0.248, h-index: 6)
AGE     Hybrid Journal   (Followers: 7, SJR: 1.358, h-index: 33)
Ageing Intl.     Hybrid Journal   (Followers: 7, SJR: 0.337, h-index: 10)
Aggiornamenti CIO     Hybrid Journal   (Followers: 1)
Aging Clinical and Experimental Research     Hybrid Journal   (Followers: 3, SJR: 0.529, h-index: 55)
Agricultural Research     Hybrid Journal   (Followers: 3)
Agriculture and Human Values     Hybrid Journal   (Followers: 12, SJR: 1.197, h-index: 49)
Agroforestry Systems     Hybrid Journal   (Followers: 19, SJR: 0.64, h-index: 56)
Agronomy for Sustainable Development     Hybrid Journal   (Followers: 10, SJR: 1.732, h-index: 59)
AI & Society     Hybrid Journal   (Followers: 7, SJR: 0.171, h-index: 19)
AIDS and Behavior     Hybrid Journal   (Followers: 13, SJR: 2.006, h-index: 71)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 4, SJR: 0.706, h-index: 19)
Akupunktur & Aurikulomedizin     Full-text available via subscription   (Followers: 1)
Algebra and Logic     Hybrid Journal   (Followers: 4, SJR: 0.566, h-index: 18)
Algebra Universalis     Hybrid Journal   (Followers: 2, SJR: 0.388, h-index: 22)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1, SJR: 0.868, h-index: 20)
Algorithmica     Hybrid Journal   (Followers: 8, SJR: 0.898, h-index: 56)
Allergo J.     Full-text available via subscription   (Followers: 1, SJR: 0.183, h-index: 20)
Allergo J. Intl.     Hybrid Journal   (Followers: 2)
Alpine Botany     Hybrid Journal   (Followers: 5, SJR: 0.729, h-index: 20)
ALTEX : Alternatives to Animal Experimentation     Open Access   (Followers: 3, SJR: 1.392, h-index: 32)
AMBIO     Hybrid Journal   (Followers: 15, SJR: 1.094, h-index: 87)
American J. of Cardiovascular Drugs     Hybrid Journal   (Followers: 15, SJR: 0.864, h-index: 39)
American J. of Community Psychology     Hybrid Journal   (Followers: 24, SJR: 1.237, h-index: 83)
American J. of Criminal Justice     Hybrid Journal   (Followers: 6, SJR: 0.634, h-index: 13)
American J. of Cultural Sociology     Hybrid Journal   (Followers: 11, SJR: 0.283, h-index: 3)
American J. of Dance Therapy     Hybrid Journal   (Followers: 4, SJR: 0.175, h-index: 13)
American J. of Potato Research     Hybrid Journal   (Followers: 2, SJR: 0.558, h-index: 35)
American J. of Psychoanalysis     Hybrid Journal   (Followers: 22, SJR: 0.293, h-index: 13)
American Sociologist     Hybrid Journal   (Followers: 13, SJR: 0.18, h-index: 13)
Amino Acids     Hybrid Journal   (Followers: 8, SJR: 1.362, h-index: 83)
AMS Review     Partially Free   (Followers: 4)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7, SJR: 0.21, h-index: 37)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 3, SJR: 0.665, h-index: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Analysis of Verbal Behavior     Hybrid Journal   (Followers: 5)
Analytical and Bioanalytical Chemistry     Hybrid Journal   (Followers: 30, SJR: 1.096, h-index: 123)
Anatomical Science Intl.     Hybrid Journal   (Followers: 2, SJR: 0.301, h-index: 26)
Angewandte Schmerztherapie und Palliativmedizin     Hybrid Journal  
Angiogenesis     Hybrid Journal   (Followers: 3, SJR: 2.212, h-index: 69)
Animal Cognition     Hybrid Journal   (Followers: 16, SJR: 1.122, h-index: 55)
Annales françaises de médecine d'urgence     Hybrid Journal   (Followers: 1, SJR: 0.156, h-index: 4)
Annales Henri Poincaré     Hybrid Journal   (Followers: 3, SJR: 1.377, h-index: 32)
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annali dell'Universita di Ferrara     Hybrid Journal   (SJR: 0.504, h-index: 14)
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1, SJR: 1.167, h-index: 26)
Annals of Behavioral Medicine     Hybrid Journal   (Followers: 11, SJR: 2.112, h-index: 98)
Annals of Biomedical Engineering     Hybrid Journal   (Followers: 18, SJR: 1.182, h-index: 94)
Annals of Combinatorics     Hybrid Journal   (Followers: 3, SJR: 0.849, h-index: 15)
Annals of Data Science     Hybrid Journal   (Followers: 9)
Annals of Dyslexia     Hybrid Journal   (Followers: 9, SJR: 0.857, h-index: 40)
Annals of Finance     Hybrid Journal   (Followers: 28, SJR: 0.686, h-index: 14)
Annals of Forest Science     Hybrid Journal   (Followers: 5, SJR: 0.929, h-index: 57)
Annals of Global Analysis and Geometry     Hybrid Journal   (Followers: 1, SJR: 1.136, h-index: 23)
Annals of Hematology     Hybrid Journal   (Followers: 14, SJR: 1.117, h-index: 62)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 6, SJR: 0.593, h-index: 42)
Annals of Microbiology     Hybrid Journal   (Followers: 10, SJR: 0.402, h-index: 26)
Annals of Nuclear Medicine     Hybrid Journal   (Followers: 5, SJR: 0.68, h-index: 45)
Annals of Operations Research     Hybrid Journal   (Followers: 8, SJR: 1.186, h-index: 78)
Annals of Ophthalmology     Hybrid Journal   (Followers: 11)
Annals of Regional Science     Hybrid Journal   (Followers: 7, SJR: 0.405, h-index: 42)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annals of Solid and Structural Mechanics     Hybrid Journal   (Followers: 10, SJR: 0.553, h-index: 8)
Annals of Surgical Oncology     Hybrid Journal   (Followers: 15, SJR: 1.902, h-index: 127)
Annals of Telecommunications     Hybrid Journal   (Followers: 7, SJR: 0.315, h-index: 25)
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1, SJR: 0.931, h-index: 31)
Antonie van Leeuwenhoek     Hybrid Journal   (Followers: 5, SJR: 0.992, h-index: 87)
Apidologie     Hybrid Journal   (Followers: 4, SJR: 1.14, h-index: 57)
APOPTOSIS     Hybrid Journal   (Followers: 8, SJR: 1.554, h-index: 87)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2, SJR: 0.354, h-index: 27)
Applications of Mathematics     Hybrid Journal   (Followers: 1, SJR: 0.274, h-index: 20)
Applied Biochemistry and Biotechnology     Hybrid Journal   (Followers: 44, SJR: 0.575, h-index: 80)
Applied Biochemistry and Microbiology     Hybrid Journal   (Followers: 17, SJR: 0.267, h-index: 26)
Applied Cancer Research     Open Access  
Applied Categorical Structures     Hybrid Journal   (Followers: 2, SJR: 0.361, h-index: 21)
Applied Composite Materials     Hybrid Journal   (Followers: 48, SJR: 0.705, h-index: 35)
Applied Entomology and Zoology     Partially Free   (Followers: 3, SJR: 0.554, h-index: 34)
Applied Geomatics     Hybrid Journal   (Followers: 3, SJR: 0.323, h-index: 9)
Applied Geophysics     Hybrid Journal   (Followers: 8, SJR: 0.541, h-index: 13)
Applied Intelligence     Hybrid Journal   (Followers: 11, SJR: 0.777, h-index: 43)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4, SJR: 0.358, h-index: 34)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 4, SJR: 0.955, h-index: 33)
Applied Mathematics - A J. of Chinese Universities     Hybrid Journal   (SJR: 0.275, h-index: 8)
Applied Mathematics and Mechanics     Hybrid Journal   (Followers: 5, SJR: 0.37, h-index: 26)
Applied Microbiology and Biotechnology     Hybrid Journal   (Followers: 62, SJR: 1.262, h-index: 161)
Applied Physics A     Hybrid Journal   (Followers: 7, SJR: 0.535, h-index: 121)
Applied Physics B: Lasers and Optics     Hybrid Journal   (Followers: 23, SJR: 0.983, h-index: 104)
Applied Psychophysiology and Biofeedback     Hybrid Journal   (Followers: 8, SJR: 0.677, h-index: 47)
Applied Research in Quality of Life     Hybrid Journal   (Followers: 10, SJR: 0.288, h-index: 15)
Applied Solar Energy     Hybrid Journal   (Followers: 16, SJR: 0.251, h-index: 6)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4, SJR: 0.351, h-index: 9)
Aquaculture Intl.     Hybrid Journal   (Followers: 22, SJR: 0.613, h-index: 40)
Aquarium Sciences and Conservation     Hybrid Journal   (Followers: 1)
Aquatic Ecology     Hybrid Journal   (Followers: 30, SJR: 0.646, h-index: 44)
Aquatic Geochemistry     Hybrid Journal   (Followers: 4, SJR: 0.764, h-index: 39)
Aquatic Sciences     Hybrid Journal   (Followers: 13, SJR: 1.172, h-index: 53)
Arabian J. for Science and Engineering     Hybrid Journal   (Followers: 5, SJR: 0.345, h-index: 20)
Arabian J. of Geosciences     Hybrid Journal   (Followers: 1, SJR: 0.417, h-index: 16)
Archaeological and Anthropological Sciences     Hybrid Journal   (Followers: 22, SJR: 1.056, h-index: 15)
Archaeologies     Hybrid Journal   (Followers: 12, SJR: 0.397, h-index: 13)
Archiv der Mathematik     Hybrid Journal   (Followers: 1, SJR: 0.597, h-index: 29)
Archival Science     Hybrid Journal   (Followers: 54, SJR: 0.804, h-index: 22)
Archive for History of Exact Sciences     Hybrid Journal   (Followers: 7, SJR: 0.28, h-index: 15)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 1, SJR: 0.946, h-index: 23)
Archive for Rational Mechanics and Analysis     Hybrid Journal   (SJR: 4.091, h-index: 66)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5, SJR: 0.865, h-index: 40)
Archives and Museum Informatics     Hybrid Journal   (Followers: 128)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4, SJR: 2.841, h-index: 40)
Archives of Dermatological Research     Hybrid Journal   (Followers: 6, SJR: 0.9, h-index: 65)
Archives of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 10, SJR: 0.846, h-index: 84)
Archives of Gynecology and Obstetrics     Hybrid Journal   (Followers: 17, SJR: 0.695, h-index: 47)
Archives of Microbiology     Hybrid Journal   (Followers: 8, SJR: 0.702, h-index: 85)
Archives of Orthopaedic and Trauma Surgery     Hybrid Journal   (Followers: 8, SJR: 1.039, h-index: 56)
Archives of Osteoporosis     Hybrid Journal   (Followers: 2, SJR: 1.092, h-index: 13)
Archives of Sexual Behavior     Hybrid Journal   (Followers: 9, SJR: 1.198, h-index: 74)
Archives of Toxicology     Hybrid Journal   (Followers: 16, SJR: 1.595, h-index: 76)
Archives of Virology     Hybrid Journal   (Followers: 5, SJR: 1.086, h-index: 90)
Archives of Women's Mental Health     Hybrid Journal   (Followers: 14, SJR: 1.264, h-index: 50)
Archivio di Ortopedia e Reumatologia     Hybrid Journal  
Archivum Immunologiae et Therapiae Experimentalis     Hybrid Journal   (Followers: 2, SJR: 1.2, h-index: 42)
ArgoSpine News & J.     Hybrid Journal   (SJR: 0.102, h-index: 3)
Argumentation     Hybrid Journal   (Followers: 5, SJR: 0.295, h-index: 18)
Arid Ecosystems     Hybrid Journal   (Followers: 3)
Arkiv för Matematik     Hybrid Journal   (Followers: 1, SJR: 0.948, h-index: 22)
Arnold Mathematical J.     Hybrid Journal   (Followers: 1)
Arthropod-Plant Interactions     Hybrid Journal   (Followers: 2, SJR: 0.797, h-index: 17)
Arthroskopie     Hybrid Journal   (Followers: 1, SJR: 0.145, h-index: 8)
Artificial Intelligence and Law     Hybrid Journal   (Followers: 10, SJR: 0.288, h-index: 25)
Artificial Intelligence Review     Hybrid Journal   (Followers: 14, SJR: 0.948, h-index: 48)
Artificial Life and Robotics     Hybrid Journal   (Followers: 8, SJR: 0.231, h-index: 14)
Asia Europe J.     Hybrid Journal   (Followers: 4, SJR: 0.247, h-index: 9)
Asia Pacific Education Review     Hybrid Journal   (Followers: 10, SJR: 0.371, h-index: 17)
Asia Pacific J. of Management     Hybrid Journal   (Followers: 14, SJR: 1.676, h-index: 50)
Asia-Pacific Education Researcher     Hybrid Journal   (Followers: 11, SJR: 0.353, h-index: 13)
Asia-Pacific Financial Markets     Hybrid Journal   (Followers: 2, SJR: 0.19, h-index: 15)
Asia-Pacific J. of Atmospheric Sciences     Hybrid Journal   (Followers: 20, SJR: 1.006, h-index: 14)
Asian Business & Management     Hybrid Journal   (Followers: 7, SJR: 0.41, h-index: 10)
Asian J. of Business Ethics     Hybrid Journal   (Followers: 7)
Asian J. of Criminology     Hybrid Journal   (Followers: 5, SJR: 0.263, h-index: 8)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2, SJR: 0.681, h-index: 15)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5, SJR: 0.195, h-index: 5)
ästhetische dermatologie & kosmetologie     Full-text available via subscription  

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Journal Cover Applied Intelligence
  [SJR: 0.777]   [H-I: 43]   [11 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1573-7497 - ISSN (Online) 0924-669X
   Published by Springer-Verlag Homepage  [2352 journals]
  • An improved DPOP algorithm based on breadth first search pseudo-tree for
           distributed constraint optimization
    • Authors: Ziyu Chen; Zhen He; Chen He
      Pages: 607 - 623
      Abstract: Abstract Depth First Search (DFS) pseudo-tree is popularly used as the communication structure in complete algorithms for solving Distributed Constraint Optimization Problems (DCOPs) from multiagent systems. The advantage of a DFS pseudo-tree lies in its parallelism derived from pseudo-tree branches because the nodes in different branches are relatively independent and can compute concurrently. However, the constructed DFS pseudo-trees in experiments often come to be chain-like and greatly impair the performances of solving algorithms. Therefore, we propose a new DPOP algorithm using a Breadth First Search (BFS) pseudo-tree as the communication structure, named BFSDPOP. Compared with a DFS pseudo-tree, a BFS pseudo-tree is more excellent on the parallelism as it has much more branches. Another notable advantage is that the height of a BFS pseudo-tree is much lower than that of a DFS pseudo-tree, which gives rise to the shorter communication paths and less communication time. The method of Cluster Removing is also presented to allocate cross-edge constraints to reduce the size of the largest message in BFSDPOP. In the experiment, BFSDPOP with a BFS pseudo-tree and original DPOP with a DFS pseudo-tree are compared on three types of problems - graph coloring problems, meeting scheduling problems and random DCOPs. The results show that BFSDPOP outperforms original DPOP in most cases, which proves the excellent attributes of BFS pseudo-tree over DFS pseudo-tree.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0905-4
      Issue No: Vol. 47, No. 3 (2017)
       
  • Fuzzy C-Means Clustering and Particle Swarm Optimization based scheme for
           Common Service Center location allocation
    • Authors: Rajan Gupta; Sunil K. Muttoo; Saibal K. Pal
      Pages: 624 - 643
      Abstract: Abstract Common Service Centers (CSCs), which are also known as Tele-centers and Rural Kiosks, are important infrastructural options for any country aiming to provide E-Governance services in rural regions. Their main objective is to provide adequate information and services to a country’s rural areas, thereby increasing government-citizen connectivity. Within developing nations, such as India, many CSC allocations are being planned. This study proposes a solution for allocating a CSC for villages in a country according to their E-Governance plan. The Fuzzy C-Means (FCM) algorithm was used for clustering the village dataset and finding a cluster center for CSC allocation, and the Particle Swarm Optimization (PSO) algorithm was used for further optimizing the results obtained from the FCM algorithm based on population. In the context of other studies addressing similar issues, this study highlights the practical implementation of location modeling and analysis. An extensive analysis of the results obtained using a village dataset from India including four prominent states shows that the proposed solution reduces the average traveling costs of villagers by an average of 33 % compared with those of allocating these CSCs randomly in a sorted order and by an average of 11 % relative to centroid allocation using the FCM-based approach only. As compared to traditional approaches like P-Center and P-Median, the proposed scheme is better by 31 % and 14 %, respectively. Therefore, the proposed algorithm yields better results than classical FCM and other types of computing techniques, such as random search & linear programming. This scheme could be useful for government departments managing the allocation of CSCs in various regions. This work should also be useful for researchers optimizing the location allocation schemes used for various applications worldwide.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0917-0
      Issue No: Vol. 47, No. 3 (2017)
       
  • Self-adaptive differential evolution algorithm with improved mutation mode
    • Authors: Shihao Wang; Yuzhen Li; Hongyu Yang
      Pages: 644 - 658
      Abstract: Abstract The optimization performance of the Differential Evolution algorithm (DE) is easily affected by its control parameters and mutation modes, and their settings depend on the specific optimization problems. Therefore, a Self-adaptive Differential Evolution algorithm with Improved Mutation Mode (IMMSADE) is proposed by improving the mutation mode of DE and introducing a new control parameters adaptation strategy. In IMMSADE, each individual in the population has its own control parameters, and they would be dynamically adjusted according to the population diversity and individual difference. IMMSADE is compared with the basic DE and the other state-of-the-art DE algorithms by using a set of 22 benchmark functions. The experimental results show that the overall performance of the proposed IMMSADE is better than the basic DE and the other compared DE algorithms.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0914-3
      Issue No: Vol. 47, No. 3 (2017)
       
  • Personalized recommendation algorithm for social networks based on
           comprehensive trust
    • Authors: Zhijun Zhang; Gongwen Xu; Pengfei Zhang; Yongkang Wang
      Pages: 659 - 669
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0928-x
      Issue No: Vol. 47, No. 3 (2017)
       
  • Bellman residuals minimization using online support vector machines
    • Authors: Gennaro Esposito; Mario Martin
      Pages: 670 - 704
      Abstract: Abstract In this paper we present and theoretically study an Approximate Policy Iteration (API) method called A P I − B R M 𝜖 using a very effective implementation of incremental Support Vector Regression (SVR) to approximate the value function able to generalize Reinforcement Learning (RL) problems with continuous (or large) state space. A P I − B R M 𝜖 is presented as a non-parametric regularization method based on an outcome of the Bellman Residual Minimization (BRM) able to minimize the variance of the problem. The proposed method can be cast as incremental and may be applied to the on-line agent interaction framework of RL. Being also based on SVR which are based on convex optimization, is able to find the global solution of the problem. A P I − B R M 𝜖 using SVR can be seen as a regularization problem using 𝜖−insensitive loss. Compared to standard squared loss also used in regularization, this allows to naturally build a sparse solution for the approximation function. We extensively analyze the statistical properties of A P I − B R M 𝜖 founding a bound which controls the performance loss of the algorithm under some assumptions on the kernel and assuming that the collected samples are not-i.i.d. following a β−mixing process. Some experimental evidence and performance for well known RL benchmarks are also presented.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0910-7
      Issue No: Vol. 47, No. 3 (2017)
       
  • An angle based constrained many-objective evolutionary algorithm
    • Authors: Yi Xiang; Jing Peng; Yuren Zhou; Miqing Li; Zefeng Chen
      Pages: 705 - 720
      Abstract: Abstract Having successfully handled many-objective optimization problems with box constraints only by using VaEA, a vector angle based many-objective evolutionary algorithm in our precursor study, this paper extended VaEA to solve generic constrained many-objective optimization problems. The proposed algorithm (denoted by CVaEA) differs from the original one mainly in the mating selection and the environmental selection, which are made suitable in the presence of infeasible solutions. Furthermore, we suggest a set of new constrained many-objective test problems which have different ranges of function values for all the objectives. Compared with normalized problems, this set of scaled ones is more applicable to test an algorithm’s performance. This is due to the nature property of practical problems being usually far from normalization. The proposed CVaEA was compared with two latest constrained many-objective optimization methods on the proposed test problems with up to 15 objectives, and on a constrained engineering problem from practice. It was shown by the simulation results that CVaEA could find a set of well converged and properly distributed solutions, and, compared with its competitors, obtained a better balance between convergence and diversity. This, and the original VaEA paper, together demonstrate the usefulness and efficiency of vector angle based algorithms for handling both constrained and unconstrained many-objective optimization problems.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0929-9
      Issue No: Vol. 47, No. 3 (2017)
       
  • Multi-objective hybrid artificial bee colony algorithm enhanced with Lévy
           flight and self-adaption for cloud manufacturing service composition
    • Authors: Jiajun Zhou; Xifan Yao
      Pages: 721 - 742
      Abstract: Abstract Service composition and optimal selection (SCOS) is a key problem in cloud manufacturing (CMfg). The present study proposed a multi-objective hybrid artificial bee colony (HABC) algorithm to address the SCOS problem in consideration of both quality of service (QoS) and energy consumption, to which an improved solution update equation with multiple dimensions of perturbation was adopted in the employed bee phase. Likewise, a cuckoo search-inspired Lévy flight was employed in the onlooker bee phase to overcome basic artificial bee colony (ABC) drawbacks such as poor exploitation and slow convergence. Moreover, a parameter adaptive strategy was applied to adjust the perturbation rate and step size of the Lévy flight to improve the performance of the algorithm. The proposed algorithm was first tested on 21 multi-objective benchmark problems and compared with four other state-of-the-art multi-objective evolutionary algorithms (MOEAs). The effect of the improvement strategies was then experimentally verified. Finally, the HABC was applied to solve multiscale SCOS problems using comparison experiments, which resulted in more competitive results and outperformed other MOEAs.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0927-y
      Issue No: Vol. 47, No. 3 (2017)
       
  • Intuitionistic fuzzy hybrid arithmetic and geometric aggregation operators
           for the decision-making of mechanical design schemes
    • Authors: Jun Ye
      Pages: 743 - 751
      Abstract: Abstract Arithmetic aggregation operators and geometric aggregation operators of intuitionistic fuzzy values (IFVs) are common aggregation operators in the fields of information fusion and decision making. However, their aggregated values imply some unreasonable results in some cases. To overcome the shortcomings, this paper proposes an intuitionistic fuzzy hybrid weighted arithmetic and geometric aggregation (IFHWAGA) operator and an intuitionistic fuzzy hybrid ordered weighted arithmetic and geometric aggregation (IFHOWAGA) operator and discusses their suitability by numerical examples. Then, we propose a multiple attribute decision-making method of mechanical design schemes based on the IFHWAGA or IFHOWAGA operator under an intuitionistic fuzzy environment. Finally, a decision-making problem regarding the mechanical design schemes of press machine is provided as a case to show the application of the proposed method.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0930-3
      Issue No: Vol. 47, No. 3 (2017)
       
  • Efficiently mining frequent itemsets with weight and recency constraints
    • Authors: Jerry Chun-Wei Lin; Wensheng Gan; Philippe Fournier-Viger; Han-Chieh Chao; Tzung-Pei Hong
      Pages: 769 - 792
      Abstract: Abstract In the past, a novel framework named recent weighted frequent itemset mining (RWFIM) and two projection-based algorithms, RWFIM-P and RWFIM-PE, were proposed to consider both the relative importance of items (item weights) and the recency of patterns. However, the projection-and-test mechanism used by these algorithms to discover recent weighted frequent itemsets (RWFIs) in a recursive way may have poor performance when the database is dense or contains long transactions. To address this issue, an efficient tree-based RWFI-Mine algorithm is proposed in this paper for mining RWFIs, which considers both weight and the recency of patterns. A novel Set-enumeration tree called the recent weighted frequent (RWF)-tree and a sorted downward closure property of RWFIs for the RWF-tree are proposed. Moreover, two data structures, named element (E)-table and recent weighted frequent (RWF)-table, are designed to store the information needed for discovering RWFIs. RFWI-Mine discovers RWFIs in a recursive way without candidate generation, thus reducing the computational costs and memory requirements for mining RWFIs. A second improved algorithm named RWFI-EMine algorithm is further proposed to avoid building E-tables and RWF-tables for unpromising itemsets and their child nodes by adopting the Estimated Weight of 2-itemset Pruning (EW2P) strategy. Extensive experiments are conducted on several real-world and synthetic datasets to evaluate the performance of the two proposed algorithms, and the ratio between the number of generated RWFIs and WFIs. Results show that the proposed algorithms outperform not only the traditional PWA algorithm for WFIM, but also the state-of-the-art RWFIM-P and RWFIM-PE algorithms for RWFIM, in terms of runtime, memory usage and scalability.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0915-2
      Issue No: Vol. 47, No. 3 (2017)
       
  • An accelerated PSO for query expansion in web information retrieval:
           application to medical dataset
    • Authors: Ilyes Khennak; Habiba Drias
      Pages: 793 - 808
      Abstract: Abstract Swarm intelligence algorithms are now among the most widely used soft computing techniques for optimization and computational intelligence. One recent swarm intelligence algorithm that has begun to receive more attention is Accelerated Particle Swarm Optimization (APSO). It is an enhanced version of PSO with global optimization capability, sufficient simplicity and high flexibility. In this paper, we propose the application of the APSO technique to efficiently solve the problem of Query Expansion (QE) in Web Information Retrieval (IR). Unlike prior studies, we introduce a new modelling of QE that aims to find the suitable expanded query from among a set of expanded query candidates. Nevertheless, due to the large number of potential expanded query candidates, it is extremely complex to produce the best one through conventional hard computing methods. Therefore, we propose to consider the problem of QE as a combinatorial optimization problem and address it with APSO. We thoroughly evaluate the proposed APSO for QE using MEDLINE, the world Web’s largest medical library. We first conduct a preliminary experiment to tune the APSO parameters. Then, we compare the results to a recent swarm intelligence algorithm called Firefly Algorithm (FA). We also compare the results with three recently published methods for QE that involved Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Bat Algorithm (BA). The experimental analysis demonstrates that the proposed APSO for QE is very competitive and yields substantial improvement over the other methods in terms of retrieval effectiveness and computational complexity.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0924-1
      Issue No: Vol. 47, No. 3 (2017)
       
  • Link prediction in fuzzy social networks using distributed learning
           automata
    • Authors: Behnaz Moradabadi; Mohammad Reza Meybodi
      Pages: 837 - 849
      Abstract: Abstract Link prediction is an area of social network research that tries to predict future links using a social network structure. This paper proposes a novel link prediction method (FLP-DLA) that is based on fuzzy social networks and distributed learning automata (DLA). Distributed learning automata are reinforcement-based optimization tools which try to learn and converge to the optimal behavior from environmental feedback using graph navigation. In the preprocessing phase of the FLP-DLA, the proposed method tries to calculate a fuzzy strength for each link based on the information of the network, such as event time. In the main phase of the FLP-DLA, it uses these fuzzy strengths in addition to DLA to determine the strength of test links. In each iteration of the proposed method, the DLA tries to find a path between the endpoints of a random test link; following this, the FLP-DLA calculates the fuzzy strength of the obtained path using the fuzzy strengths of the links through the path, and rewards or penalizes the DLA based on the path strength. The main phase is repeated until the LAs converge to an action. Finally, we use the strength of the test links as the output of the link prediction. The results reported in this paper have proven satisfactory, indicating the usefulness of the proposed method for some social network datasets.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0933-0
      Issue No: Vol. 47, No. 3 (2017)
       
  • Human mental search: a new population-based metaheuristic optimization
           algorithm
    • Authors: Seyed Jalaleddin Mousavirad; Hossein Ebrahimpour-Komleh
      Pages: 850 - 887
      Abstract: Abstract Population-based metaheuristic algorithms have become popular in recent years with them getting used in different fields such as business, medicine, and agriculture. The present paper proposes a simple but efficient population-based metaheuristic algorithm called Human Mental Search (HMS). HMS algorithm mimics the exploration strategies of the bid space in online auctions. The three leading steps of HMS algorithm are: (1) the mental search that explores the region around each solution based on Levy flight, (2) grouping that determines a promising region, and (3) moving the solutions toward the best strategy. To evaluate the efficiency of HMS algorithm, some test functions with different characteristics are studied. The results are compared with nine state-of-the-art metaheuristic algorithms. Moreover, some nonparametric statistical methods, including Wilcoxon signed rank test and Friedman test, are provided. The experimental results demonstrate that the HMS algorithm can present competitive results compared to other algorithms.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0903-6
      Issue No: Vol. 47, No. 3 (2017)
       
  • Cooperative co-evolution with sensitivity analysis-based budget assignment
           strategy for large-scale global optimization
    • Authors: Sedigheh Mahdavi; Shahryar Rahnamayan; Mohammad Ebrahim Shiri
      Pages: 888 - 913
      Abstract: Abstract Cooperative co-evolution has proven to be a successful approach for solving large-scale global optimization (LSGO) problems. These algorithms decompose the LSGO problems into several smaller subcomponents using a decomposition method, and each subcomponent of the variables is optimized by a certain optimizer. They use a simple technique, the round-robin method, to equally assign the computational time. Since the standard cooperative co-evolution algorithms allocate the computational budget equally, the performance of these algorithms deteriorates for solving LSGO problems with subcomponents by various effects on the objective function. For this reason, it could be very useful to detect the subcomponents’ effects on the objective function in LSGO problems. Sensitivity analysis methods can be employed to identify the most significant variables of a model. In this paper, we propose a cooperative co-evolution algorithm with a sensitivity analysis-based budget assignment method (SACC), which can allocate the computational time among all subcomponents based on their different effects on the objective function, accordingly. SACC is benchmarked on imbalanced LSGO problems. Simulation results confirm that SACC obtains a promising performance on the majority of the imbalanced LSGO benchmark functions.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0926-z
      Issue No: Vol. 47, No. 3 (2017)
       
  • LinGraph: a graph-based automated planner for concurrent task planning
           based on linear logic
    • Authors: Sıtar Kortik; Uluc̣ Saranli
      Pages: 914 - 934
      Abstract: Abstract In this paper, we introduce an automated planner for deterministic, concurrent domains, formulated as a graph-based theorem prover for a propositional fragment of intuitionistic linear logic, relying on the previously established connection between intuitionistic linear logic and planning problems. The new graph-based theorem prover we introduce improves planning performance by reducing proof permutations that are irrelevant to planning problems particularly in the presence of large numbers of objects and agents with identical properties (e.g. robots within a swarm, or parts in a large factory). We first present our graph-based automated planner, the Linear Logic Graph Planner (LinGraph). Subsequently we illustrate its application for planning within a concurrent manufacturing domain and provide comparisons with four existing automated planners, BlackBox, Symba-2, Metis and the Temporal Fast Downward (TFD), covering a wide range of state-of-the-art automated planning techniques and implementations. We show that even though LinGraph does not rely on any heuristics, it still outperforms these systems for concurrent domains with large numbers of identical objects and agents. These gains persist even when existing methods on symmetry reduction and numerical fluents are used, with LinGraph capable of handling problems with thousands of objects. Following these results, we also show that plan construction with LinGraph is equivalent to multiset rewriting systems, formally relating LinGraph to intuitionistic linear logic.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0936-x
      Issue No: Vol. 47, No. 3 (2017)
       
  • Using differential evolution strategies in chemical reaction optimization
           for global numerical optimization
    • Authors: Mourad Nouioua; Zhiyong Li
      Pages: 935 - 961
      Abstract: Abstract In this paper we propose a new hybrid metaheuristic approach which combines Chemical Reaction Optimization and Differential Evolution to solve global numerical optimization problems. Chemical Reaction Optimization is widely used in several optimization problems. However, due to its random behavior in searching the optimal solution, it may converge slowly. Differential Evolution is another efficient method based on differentiation operation which can be achieved by several, more or less selective, research strategies. The aim of this paper is to propose new hybrid algorithms that use Differential Evolution strategies inside Chemical Reaction Optimization process in order to overcome its limits by increasing optimal quality and accelerating convergence. We propose in this paper two new hybrid algorithms. Both of them use the Differential Evolution Best Strategy as a local search operator to improve the exploitation process and the Differential Evolution Random Strategy as a global search operator to maintain the diversity of the population and improve the exploration process. However, the two proposed algorithms slightly differ on the used local search operators. Based on 23 benchmark functions classified in 3 categories, experimental studies start by showing that our second proposed algorithm is better than the first one. Then, this second algorithm is compared with numerous other existing algorithms. First, the experimental results of comparison with the original algorithms show that our algorithm attains very good performance for (1) the quality of the obtained solutions, where it outperforms the other algorithms by achieving the first average and overall rank for two over the three categories; (2) for the robustness where it obtains the best average number of successful runs (21.47 over 25 runs) as well as for (3) convergence speed where our proposed algorithm converges faster comparing with other algorithms in nine over the twenty three functions and finds better solution for functions where other algorithms converge faster. In addition, the proposed algorithm has also been compared with other hybrid chemical reaction and differential evolution based algorithms, the experimental results show that globally the proposed algorithm also outperforms the other hybrid algorithms except for some limited cases.
      PubDate: 2017-10-01
      DOI: 10.1007/s10489-017-0921-4
      Issue No: Vol. 47, No. 3 (2017)
       
  • A human-like visual-attention-based artificial vision system for wildland
           firefighting assistance
    • Authors: Kurosh Madani; Viachaslau Kachurka; Christophe Sabourin; Veronique Amarger; Vladimir Golovko; Lucile Rossi
      Abstract: Abstract In this work we contribute to development of a “Human-like Visual-Attention-based Artificial Vision” system for boosting firefighters’ awareness about the hostile environment in which they are supposed to move along. Taking advantage from artificial visual-attention, the investigated system’s conduct may be adapted to firefighter’s way of gazing by acquiring some kind of human-like artificial visual neatness supporting firefighters in interventional conditions’ evaluation or in their appraisal of the rescue conditions of people in distress dying out within the disaster. We achieve such a challenging goal by combining a statistically-founded bio-inspired saliency detection model with a Machine-Learning-based human-eye-fixation model. Hybridization of the two above-mentioned models leads to a system able to tune its parameters in order to fit human-like gazing of the inspected environment. It opens appealing perspectives in computer-aided firefighters’ assistance boosting their awareness about the hostile environment in which they are supposed to evolve. Using as well various available wildland fires images’ databases as an implementation of the investigated concept on a 6-wheeled mobile robot equipped with communication facilities, we provide experimental results showing the plausibility as well as the efficiency of the proposed system.
      PubDate: 2017-10-09
      DOI: 10.1007/s10489-017-1053-6
       
  • A multi-objective assembly line balancing problem with worker’s skill
           and qualification considerations in fuzzy environment
    • Authors: Maryam Salehi; Hamid Reza Maleki; Sadegh Niroomand
      Abstract: Abstract In this study a new multi-objective assembly line balancing problem is studied. Objectives like the number of stations, the equipment purchasing cost, the worker time dependent wage, and worker dependent dis-quality level of the stations is to be minimized simultaneously with worker allocation and equipment assignment possibilities. The problem also is formulated in a fuzzy environment. To solve such problem, a new hybrid fuzzy interactive approach is proposed in two stages. In the first stage, the fuzzy formulation is converted to a crisp multi-objective formulation using a credibility-based chance constrained programming approach. Then in the second stage, the obtained crisp multi-objective formulation is solved by a new hybrid fuzzy programming approach. To evaluate the proposed approach, two generated examples and a case study from garment production industries are used for computational experiments. The extensive computational study prove the superiority of the proposed approach over the well-known approaches of the literature.
      PubDate: 2017-10-07
      DOI: 10.1007/s10489-017-1065-2
       
  • Robust discriminative feature learning with calibrated data reconstruction
           and sparse low-rank model
    • Authors: Tingjin Luo; Yang Yang; Dongyun Yi; Jieping Ye
      Abstract: Abstract Since large amounts of labeled high-dimensional data needed to be processed, supervised feature learning has become an important and challenging problem in machine learning. Conventional supervised methods often adopt ℓ 2-norm loss function, which is sensitive to the outliers. However, real world data always contain lots of outliers that make traditional supervised methods fail to achieve the optimal performance. In addition, these methods can not reconstruct the original complex structured data well, since the dimensions of their learned projection matrices are often limited to the number of classes and are sub-optimal. To address these challenges, we propose a novel robust discriminative feature learning (RDFL) method via calibrated data reconstruction and sparse low-rank model. Specifically, RDFL preserves the discriminant information and simultaneously reconstructs the complex low-rank structure by minimizing joint ℓ 2,1-norm reconstruction error and within-class distance. To solve the proposed non-smooth problem, we derive an efficient optimization algorithm to soften the contributions of outliers. Meanwhile, we adopt the general power iteration method (GPIM) to accelerate our algorithm to make it scalable to large scale problem and theoretically analyze the convergence and computational complexity of the proposed algorithm. Extensive experimental results present that our proposed RDFL outperforms other compared methods in most cases and significantly improve the robust performance to noise and outliers.
      PubDate: 2017-10-07
      DOI: 10.1007/s10489-017-1060-7
       
  • Connection number of set pair analysis based TOPSIS method on
           intuitionistic fuzzy sets and their application to decision making
    • Authors: Kamal Kumar; Harish Garg
      Abstract: Abstract Intuitionistic fuzzy set plays a significant role to handle the uncertainties in the data during the decision-making process. Keeping the advantage of it in mind, an attempt has been made in the present article for rating the different preferences of the object based on the set pair analysis (SPA). For this, a major component of SPA, known as a connection number, has been constructed based on the preference values and the comprehensive ideal values of the object. An extension of TOPSIS method is further developed, based on the proposed connection number of SPA, to calculate relative-closeness of sets of alternatives which are used to generate the ranking order of the alternatives. A real example is taken to demonstrate the applicability and validity of the proposed methodology.
      PubDate: 2017-10-02
      DOI: 10.1007/s10489-017-1067-0
       
  • Generalized interaction aggregation operators in intuitionistic fuzzy
           multiplicative preference environment and their application to
           multicriteria decision-making
    • Authors: Harish Garg
      Abstract: Abstract The main objective of this manuscript is to present a new preference relation called the intuitionistic fuzzy multiplicative preference relation. Under this, some series of new aggregation operators, by overcoming the shortcomings of some existing operators, have been defined. As most of the aggregation operators have been constructed under the intuitionistic fuzzy preference relation which deals with the conditions that the attribute values grades are symmetrical and uniformly distributed. In this manuscript, these assumptions have been relaxed by distributing the attribute grades to be asymmetrical around 1 and hence under it, some series of aggregation operators, namely intuitionistic fuzzy multiplicative interactive weighted, ordered weighted and hybrid weighted averaging operators have been proposed. Various desirable properties of these operators have also been discussed in details. A group decision-making method has been presented, based on the proposed operators, for ranking the different alternatives. A real example is taken to demonstrate the applicability and validity of the proposed methodology.
      PubDate: 2017-10-02
      DOI: 10.1007/s10489-017-1066-1
       
 
 
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