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 Subjects -> ENGINEERING (Total: 2156 journals)     - CHEMICAL ENGINEERING (186 journals)    - CIVIL ENGINEERING (168 journals)    - ELECTRICAL ENGINEERING (93 journals)    - ENGINEERING (1164 journals)    - ENGINEERING MECHANICS AND MATERIALS (355 journals)    - HYDRAULIC ENGINEERING (55 journals)    - INDUSTRIAL ENGINEERING (54 journals)    - MECHANICAL ENGINEERING (81 journals) ENGINEERING (1164 journals)            First | 3 4 5 6 7 8 9 10 | Last
 Journal of Advanced Manufacturing Systems       (Followers: 5) Journal of Aerosol Science       (Followers: 1) Journal of Aerospace Engineering       (Followers: 49) Journal of Alloys and Compounds       (Followers: 8) Journal of Analytical and Applied Pyrolysis       (Followers: 3) Journal of Analytical Science & Technology       (Followers: 5) Journal of Analytical Sciences, Methods and Instrumentation       (Followers: 1) Journal of Applied Analysis Journal of Applied and Industrial Sciences Journal of Applied Logic Journal of Applied Physics       (Followers: 82) Journal of Applied Probability       (Followers: 6) Journal of Applied Research and Technology Journal of Applied Science and Technology Journal of Applied Sciences       (Followers: 5) Journal of Architectural Engineering       (Followers: 6) Journal of ASTM International       (Followers: 3) Journal of Automation and Control       (Followers: 1) Journal of Aviation Technology and Engineering       (Followers: 6) Journal 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Technology Journal of Industrial and Production Engineering       (Followers: 3) Journal of Industrial Engineering and Management       (Followers: 4) Journal of Inequalities and Applications Journal of Infrared, Millimeter and Terahertz Waves       (Followers: 1) Journal of Inverse and Ill-posed Problems       (Followers: 1)
 Journal of Mathematical Modelling and Algorithms   [SJR: 0.358]   [H-I: 19]   [2 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1570-1166 - ISSN (Online) 1572-9214    Published by Springer-Verlag  [2292 journals]
• Reducing the Structure Space of Bayesian Classifiers Using Some General
Algorithms
• Abstract: Abstract The use of Bayesian Networks (BNs) as classifiers in different application fields has recently witnessed a noticeable growth. Yet, using the Naïve Bayes application, and even the augmented Naïve Bayes, to classifier-structure learning, has been vulnerable to some extent, which accounts for the resort of experts to other more sophisticated types of algorithms. Consequently, the use of such algorithms has paved the way for raising the problem of super-exponential increase in computational complexity of the Bayesian classifier learning structure, with the increasing number of descriptive variables. In this context, the main objective of our present work lies in trying to conceive further solutions to solve the problem of the intricate algorithmic complexity imposed during the learning of Bayesian classifiers structure through the use of sophisticated algorithms. Our results revealed that the newly suggested approach allows us to considerably reduce the execution time of the Bayesian classifier structure learning without any information loss.
PubDate: 2015-06-01

• Sufficiency and Duality for Nonsmooth Multiobjective Programming Problems
Involving Generalized (Φ, ρ )- V -Type I Functions
• Abstract: Abstract In this paper, a class of nonsmooth multiobjective programming problems is considered. We introduce the new concepts of (Φ, ρ)-V-type I, (pseudo, quasi) (Φ, ρ)-V-type I and (quasi, pseudo) (Φ, ρ)-V-type I functions, in which the involved functions are locally Lipschitz. Based upon these generalized (Φ, ρ)-V-type I functions, the sufficient optimality conditions for weak efficiency, efficiency and proper efficiency are derived. Mond-Weir duality results are also established under the aforesaid functions.
PubDate: 2015-06-01

• Multi-period Possibilistic Mean Semivariance Portfolio Selection with
Cardinality Constraints and its Algorithm
• Abstract: Abstract In this paper, we consider a multi-period portfolio selection problem in a fuzzy investment environment, in which the return and risk of assets are characterized by possibilistic mean value and possibilistic semivariance, respectively. Based on the theories of possibility, a new multi-period possibislistic portfolio selection model is proposed, which contains risk control, transaction costs, borrowing constraints, threshold constraints and cardinality constraints. the proposed model can be transformed into a crisp nonlinear dynamic optimization problem by using fuzzy programming approach. Because of the transaction costs and cardinality constraints, the multi-period portfolio selection is a mix integer dynamic optimization problem with path dependence A forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, a comparison analysis of the different cardinality constraints is provided to illustrate the efficiency of the proposed approaches and the designed algorithm.
PubDate: 2015-06-01

• Partial Solutions and MultiFit Algorithm for Multiprocessor Scheduling
• Abstract: Abstract A new polynomial algorithm is developed for the classical multiprocessor scheduling problem in which independent jobs are nonpreemptively scheduled on identical parallel machines with the objective of minimizing the makespan, i.e. the latest job finishing time. The algorithm at first generates and merges a set of partial solutions in order to obtain a feasible solution for the multiprocessor scheduling problem. Then a set of bin packing problems are solved in order to improve the solution, by iteratively using a M u l t i F i t type procedure on different job sets. The effectiveness of this approach is evaluated by solving a large number of benchmark instances. The results indicate that the proposed algorithm, called PSMF, is very competitive with well known constructive algorithms for a wide range of instances. Furthermore, PSMF is competitive with respect to some of the best heuristics for parallel machine scheduling problems only when it uses a 2-exchange procedure.
PubDate: 2015-06-01

• On Soft Power Diagrams
• Abstract: Abstract Many applications in operations research begin with a set of points in a Euclidean space that is partitioned into clusters. Common data analysis tasks then are to devise a classifier deciding to which of the clusters a new point is associated, finding outliers with respect to the clusters, or identifying the type of clustering used for the partition. One of the common kinds of clusterings are (balanced) least-squares assignments with respect to a given set of sites. For these, there is a ‘separating power diagram’ for which each cluster lies in its own cell. In the present paper, we aim to develop new, efficient algorithms for outlier detection and the computation of thresholds that measure how similar a clustering is to a least-squares assignment for fixed sites. For this purpose, we devise a new model for the computation of a ‘soft power diagram’, which allows a soft separation of the clusters with ‘point counting properties’; e.g. we are able to prescribe the maximum number of points we wish to classify as outliers. As our results hold for a more general non-convex model of free sites, we describe it and our proofs in this more general way. We show that its locally optimal solutions satisfy the aforementioned point counting properties, by studying the corresponding optimality conditions. For our target applications that use fixed sites, our algorithms are efficiently solvable to global optimality by linear programming.
PubDate: 2015-06-01

• Upgrading p -Median Problem on a Path
• Abstract: Abstract Upgrading p-median problem is a problem of finding the best median of the given graph through modification of its parameters. The current paper develops a polynomial-time model to address this problem when the weights of vertices can be varying under a given budget. Moreover, in the case where the considering graph has a special structure, namely a path, a linear time algorithm will be proposed for solving the problem with uniform cost.
PubDate: 2015-06-01

• Planning a Capacitated Road Network with Flexible Travel Times: A Genetic
Algorithm
• Abstract: Abstract We are concerned with a capacitated location-multi allocation-routing problem in a road network with flexible travel times. It is assumed that all links are two-way and capacities of the server nodes and arcs for accepting of population are limited. The aim of our work is to find numbers and locations of server nodes, allocation of the existing population in existing demand nodes on the network to the servers and the allocation of existing population in each node to different routes to determine the decided server for each member so that total transportation time is minimized. Here, two basic concepts are considered: multi allocation and flexible travel times. The concept of multi allocation arises from the possibility of allocating the existing population in a demand node to more than one server node. Also, flexible travel times concentrate on impact of traveling population on the times of links simultaneously, that is, depending on how the population is distributed on the network, the travel times on links may be increased. So, to have the least increase in the time of each link, it is necessary to decide upon the distribution of population in the network. We formulate the proposed problem as a mixed-integer nonlinear programming model and then present a genetic algorithm (GA) for solving large problems Finally, we make two sets of numerical experiments and analyze the obtained results by LINGO solver and GA. Numerical results show the proposed GA to be highly efficient.
PubDate: 2015-05-19

• L (0,1)-labelling of Permutation Graphs
• Abstract: Abstract L(0,1)-labelling of a graph G=(V,E) is a function f from the vertex set V(G) to the set of non-negative integers such that adjacent vertices get number zero apart, and vertices at distance two get distinct numbers. The goal of L(0,1)-labelling problem is to produce a legal labelling that minimize the largest label used. In this article, it is shown that, for a permutation graph G with maximum vertex degree Δ, the upper bound of λ 0,1(G) is Δ−1. Finally, we prove that the result is exact for bipartite permutation graph.
PubDate: 2015-05-01

• Fuzzy Geometric Programming Approach in Multivariate Stratified Sample
Surveys Under Two Stage Randomized Response Model
• Abstract: Abstract This paper provide a profound study on optimum allocation of two stage multivariate stratified Warner’s randomized response (RR) model with linear and non linear cost function. The multi-objective problem is formulated as a Geometric Programming Problem (GPP). The fuzzy programming approach is adopted to solve the formulated problem. A numerical example is given to illustrate the computational details of the suggested method.
PubDate: 2015-04-22

• GPU implementation of Jacobi Method and Gauss-Seidel Method for Data
Arrays that Exceed GPU-dedicated Memory Size
• Abstract: Abstract The paper proposes a method to extend the dimension of grids that GPU-aided implicit finite difference method is capable to work with. The approach is based on the pyramid method. A predictive mathematical model for computation duration is proposed. This model allows to find optimal algorithm parameters. The paper provides computation experiment results that has shown the model to be accurate enough to predict optimal algorithm parameters.
PubDate: 2015-04-21

• Partial Trade Credit Policy of Retailer in Economic Order Quantity Models
for Deteriorating Items with Expiration Dates and Price Sensitive Demand
• Abstract: Abstract In a supplier-retailer-customer supply chain, a credit-worthy retailer frequently receives a permissible delay on the entire purchase amount without collateral deposits from his/her supplier (i.e., an up-stream full trade credit). By contrast, a retailer usually requests his/her credit-risk customers to pay a fraction of the purchase amount at the time of placing an order, and then grants a permissible delay on the remaining balance (i.e., a down-stream partial trade credit). Also, in selecting an item for use, the selling price of that item is one of the decisive factors to the customers. It is well known that the higher selling price of item decreases the demand rate of that item where the lesser price has the reverse effect. Hence, the demand rate of an item is dependent on the selling price of that item. In addition, many products such as fruits, vegetables, high-tech products, pharmaceuticals, and volatile liquids not only deteriorate continuously due to evaporation, obsolescence and spoilage but also have their expiration dates. However, only a few researchers take the expiration date of a deteriorating item into consideration. This paper proposes an economic order quantity model to allow for: (a) the strategy that supplier offers retailer a full trade credit policy whereas the retailer offers their customers a partial trade credit policy, (b) selling price dependent demand rate, (c) a profit maximization objective and (d) deteriorating items not only deteriorate continuously but also have their expiration dates. For the objective function sufficient conditions for the existence and uniqueness of the optimal solution are provided. An efficient algorithm is designed to determine the optimal pricing and inventory policies for the retailer. Finally, numerical examples are presented to illustrate the proposed model and the effect of key parameters on optimal solution is examined.
PubDate: 2015-04-19

• An Adaptive Trust Region Method Based on Simple Conic Models
• Abstract: Abstract A new adaptive trust region algorithm with simple conic models is proposed. By use of the simple conic model, the new method needs less memory capacitance and computational complexity. The nonmonotone and adaptive techniques are introduced to improve the efficiency of the proposed algorithm. The convergence results of the method are proved under certain conditions. Numerical tests show that the new algorithm is efficient and robust.
PubDate: 2015-03-26

• A New Search Procedure for the Two-dimensional Orthogonal Packing Problem
• Abstract: Abstract In this paper we propose a new exact procedure for the two-dimensional orthogonal packing problem, based on F. Clautiaux et al. approach (Clautiaux et al. Eur. J. Oper. Res. 183(3), 1196–1211, 2007). The principle consists in searching first the positions of the items on the horizontal axis, so as that, at each position, the sum of the heights of the items does not exceed the height of the bin. Each time a valid placement of all the items is encountered, another procedure determines if it can be extended to a solution of the packing problem, searching the positions of the items on the vertical axis. Novel aspects of our approach include a simple and efficient search procedure, which only generates restricted placements, at least in a first stage, in order to reduce the search space, and the memorization of unsuccessful configurations, which are then used to detect dead-ends. We tested our implementation on a selection of orthogonal packing problems and strip packing problems, and we compared our results with those of recent successful approaches.
PubDate: 2015-03-14

• Solving the Nonlinear Power Flow Problem Through General Solutions of
Under-determined Linearised Systems
• Abstract: Abstract This work focuses on the solution of a set of algebraic nonlinear equations representing the steady state operation of electrical power systems. The classical modelling of the so-called power flow problem requires the statement of the power balance equations and the specification of some network variables. Usually Newton method is applied to solve these equations, which requires the solution of a linear system at each iteration. Here, the formulation of the power flow problem is modified by increasing the number of variables to be computed, such that an under-determined linear system is solved at each iteration. This strategy imparts flexibility to obtain solutions with respect to selected performance indexes. Numerical results obtained with test-systems ranging from 26 to 1916 equations and 30 to 2013 variables illustrate the main features of the proposed application.
PubDate: 2015-03-08

• An Adaptive Infeasible Interior-Point Algorithm with Full Nesterov-Todd
Step for Semidefinite Optimization
• Abstract: Abstract We present an adaptive full Nesterov-Todd step infeasible interior-point method for semidefinite optimization. The proposed algorithm requires two types of full Nesterov-Todd steps are called, feasibility steps and centering steps, respectively. At each iteration both feasibility and optimality are reduced exactly at the same rate. In each iteration of the algorithm we use the largest possible barrier parameter value θ. The value θ varies from iteration to iteration and it lies between the two values $$\frac {1}{4n}$$ and $$\frac {1}{5n}$$ , which results a faster algorithm.
PubDate: 2015-03-01

• Higher Order Fractional Symmetric Duality Over Cone Constraints
• Abstract: Abstract In this paper, a pair of Mond-Weir type higher order fractional symmetric dual program over cone constraints is formulated. Under higher order invexity assumptions, we prove weak, strong and strict duality theorems. Moreover, a self dual program is formulated and self duality theorem is discussed.
PubDate: 2015-03-01

• Derivative-Free Augmented Lagrangian for Global Optimization: Cost
Minimization in a Simplified Activated Sludge System Model
• Abstract: Abstract A methodology for finding the optimal values of the decision variables from an efficient simplified mathematical model of an activated sludge system is addressed in this paper. The work herein presented arises in a wastewater treatment plant design context, where investment and operational costs are to be minimized and computational effort is to be reduced. To achieve the best design, a non-linear optimization solution method based on an augmented Lagrangian approach is proposed. At each iteration, a subproblem is globally solved by a derivative-free recursive branching technique, known as the multilevel coordinate search algorithm of Huyer and Neumaier [20]. The presented technique has been shown to work quite well when solving the herein proposed non-convex and non-smooth constrained optimization model. The numerical results show the reliability of the obtained solutions at a reduced computational cost.
PubDate: 2015-03-01

• Optimal Preservation Technology Investment, Retail Price and Ordering
Policies for Deteriorating Items under Trended Demand and Two Level Trade
Credit Financing
• Abstract: Abstract This research analyzes the impact of deploying suitable preservation technology for an inventory system in which units are subject to constant rate of deterioration. The demand is considered to be function of time and retail price. It is assumed that the supplier offers a fixed credit period to the retailer and retailer also offers credit period to the customers. The goal is to maximize the total profit per unit time with respect to optimal investment to be made in preservation technology, retail price of an item and purchase quantity. The concavity of the total profit is validated using numerical example. The managerial issues are discussed.
PubDate: 2015-03-01

• ILIGRA: An Efficient Inverse Line Graph Algorithm
• Abstract: Abstract This paper presents a new and efficient algorithm, IligraLIGRA, for inverse line graph construction. Given a line graph H, ILIGRA constructs its root graph G with the time complexity being linear in the number of nodes in H. If ILIGRA does not know whether the given graph H is a line graph, it firstly assumes that H is a line graph and starts its root graph construction. During the root graph construction, ILIGRA checks whether the given graph H is a line graph and ILIGRA stops once it finds H is not a line graph. The time complexity of ILIGRA with line graph checking is linear in the number of links in the given graph H. For sparse line graphs of any size and for dense line graphs of small size, numerical results of the running time show that ILIGRA outperforms all currently available algorithms.
PubDate: 2015-03-01

• Second-Order Nondifferentiable Multiobjective Mixed Symmetric Dual
Programs Over Cones
• Abstract: Abstract In this paper, a pair of second-order mixed symmetric nondifferentiable multiobjective dual programs over arbitrary cones where each of the objective functions contains a pair of support functions is considered. Further, weak, strong and converse duality theorems are established under the assumptions of second-order K- (F,ρ)-convexity. Moreover, we have illustrated a numerical example which is second-order K- (F,ρ)-convex but not second-order F-convex. Several special cases are also obtained.
PubDate: 2015-03-01

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