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Journal Cover International Journal of Fuzzy Computation and Modelling
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   Hybrid Journal Hybrid journal (It can contain Open Access articles)
     ISSN (Print) 2052-353X - ISSN (Online) 2052-3548
     Published by Inderscience Publishers Homepage  [390 journals]
  • Strong solvability of linear interval systems of inequalities with simple
           dependencies
    • Authors: Chigozie Francolins Uzoh, Okey D. Onukwuli, Joseph Tagbo Nwabanne, Philo P.K. Igbokwe
      Pages: 3 - 14
      Abstract: This paper is concerned with strong solvability of linear interval inequalities. In traditional interval analysis, we suppose that values from different intervals are mutually independent. But this assumption can be sometimes too restrictive. We derive extensions of classical results for the case when there is a simple dependence structure between coefficients of an interval system. The dependency is given by equality of two sub-matrices of the constraint matrix. We apply the approach to strong solvability of complex interval linear systems of inequalities.
      Keywords: interval matrix; strong solutions; linear interval inequalities; dependencies
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 3 - 14
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064239
      Issue No: Vol. 1, No. 1 (2014)
       
  • Multi-objective fuzzy job shop scheduling
    • Authors: Manjeet Singh, Gürsel A. Süer, Feyzan Arikan
      Pages: 15 - 36
      Abstract: The job shop scheduling problem (JSSP) deals with determining schedule for each resource/machine under job and machine flow restrictions such that the selected objective function is satisfied. Multi-objective scheduling is widely used to obtain desirable results in the existence of more than one performance measure in scheduling problems. The paper focuses on multi-objective scheduling in a job shop environment. One of the useful methods in multi-objective environment is the use of fuzzy operators in modelling the system. Fuzzy operators provide the model with characteristics where user can input desired bounds for all of the performance measures with suitable membership functions. In this study, three mathematical models are presented and combined as a multiple objective scheduling model where the considered three objectives are minimising number of tardy jobs, total tardiness and maximum tardiness, respectively. For the solution of the model, fuzzy programming is utilised by using min operator and augmented max-min operator. The model with augmented max min operator found only non-dominated solutions. Then mathematical model optimising two performance measure is also discussed. The quality between solutions obtained from math model optimising two performance measures model versus three performance measures is also discussed.
      Keywords: job shop scheduling; fuzzy theory; non-dominated solutions; multi-objective scheduling; fuzzy scheduling; fuzzy logic; mathematical modelling; performance measures
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 15 - 36
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064225
      Issue No: Vol. 1, No. 1 (2014)
       
  • Adaptive fuzzy controller for controlling the dynamics of robot motion
    • Authors: Vaishali Sood, Parveen Kumar
      Pages: 37 - 50
      Abstract: Autonomous robots are of prime importance in everyday life because of their capability to handle the non-linear situations. This paper describes the autonomous robot motion control system based on fuzzy logic proportional integral (PI) controller that reaches to its target value faster than others. Fuzzy rules are embedded in the controller to tune the gain parameters of PI controller and to move the robot along the task trajectory with variation in heading angle (θ) towards the target to make it helpful in real time applications. It discusses the design aspects of the fuzzy PI controller for controlling the dynamics of autonomous robot that have higher distribution rejection properties (DRP), low settling time (ST) and high adaptability towards the variation in the angle towards the target. The performance of a robot (RM) has been verified using MATLAB and results obtained have been found to be robust. Overall, the performances criteria in terms of its response towards ST, target acquisition (TA) and DRP have been found to be good.
      Keywords: autonomous robots; fuzzy modelling; distribution rejection properties; DRP; settling time; stability; target acquisition; adaptive control; fuzzy control; robot control; robot dynamics; robot motion; fuzzy PI controllers
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 37 - 50
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064230
      Issue No: Vol. 1, No. 1 (2014)
       
  • Standard orthogonal polynomials-based solution of fuzzy differential
           equations
    • Authors: Snehashish Chakraverty, Smita Tapaswini
      Pages: 51 - 71
      Abstract: This paper proposes a new method to solve n<SUP align="right">th</SUP> order fuzzy differential equations using collocation type of method. In the solution procedure Legendre polynomials are used in the collocation method. Three different cases have been considered for the analysis. Known example problems are solved using the proposed procedure. Obtained results are compared with the exact solution in order to illustrate the efficiency and reliability of the proposed method. Solutions are depicted in term of figures and tables.
      Keywords: Gaussian fuzzy numbers; Legendre polynomials; nth order; fuzzy differential equations; FDEs; fuzzy logic; orthogonal polynomials; collocation.
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 51 - 71
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064236
      Issue No: Vol. 1, No. 1 (2014)
       
  • A fuzzy differential approach to a two plants
           production-recycling-disposal inventory problem via genetic
           algorithms
    • Authors: Dipak Kumar Jana, M. Maiti, T.K. Roy
      Pages: 72 - 96
      Abstract: This paper develops a production, recycling-disposal inventory problem over a finite time horizon. The production and recycling process are performed in separate plants which are located very near to the market. The products are continuously transferred to the market. Here, the dynamic demand is satisfied by production and recycling. Recycling products can be used as new products which are sold again in the market. The rate of production, recycling and disposal are assumed to be function of time. The setup cost, idle cost and environment pollution recovery cost for production-recycling system in industry are also included. Model is formulated using fuzzy differential equation. Two different approaches are used in this model as: 1) modified graded mean integration value (MGMIV); 2) fuzzy preference ordering of intervals (FPOI). A genetic algorithm with binary mode representation, roulette wheel selection and random mutation process are applied. The optimum results are presented in tabular form and graphically.
      Keywords: fuzzy differential equations; production; recycling; disposal; idle cost; environmental protection costs; genetic algorithms; inventory modelling
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 72 - 96
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064228
      Issue No: Vol. 1, No. 1 (2014)
       
  • A fuzzy-based routing protocol for cognitive radio networks
    • Authors: Vivek Kukreja, Shailender Gupta, Bharat Bhushan
      Pages: 97 - 122
      Abstract: With the growing spectrum demand over the last decade, the use of cognitive radio networks (CRN) has provided a viable solution to spectrum scarcity problem. These networks basically employ two types of users: primary user (PU) and secondary user (SU). The PUs are allocated a license to use the spectrum at their will. On the other hand the SUs communicates via other SUs or through the licensed spectrum of PU nodes opportunistically. In such a scenario it is important that routing protocol that is deployed must take into consideration the stability of the route. Therefore, this paper proposes a novel fuzzy-based routing strategy with this objective in mind. Further, an attempt has been made to evaluate the performance of proposed routing strategy in realistic environment. The simulation results shows that the path selection utilising the fuzzy theory presents far better results when compared with shortest path routing protocol employing CR capabilities.
      Keywords: fuzzy logic controllers; FLCs; cognitive radio networks; CRNs; ad-hoc networks; realistic environment; Dijikstra algorithm; fuzzy routing protocols; fuzzy control
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 1 (2014) pp. 97 - 122
      PubDate: 2014-08-09T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.064227
      Issue No: Vol. 1, No. 1 (2014)
       
 
 
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