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Information Journal Paper

Title

AN ANALYTICAL AND COMPARATIVE APPROACH FOR USING METAHEURISTIC ALGORITHMS FOR JOB SHOP SCHEDULING PROBLEMS

Pages

  63-76

Keywords

TABU SEARCH (TS)Q1
SIMULATED ANNEALING (SA)Q1
GENETIC ALGORITHM(GA)Q1
PARTICLE SWARM OPTIMIZATION(PSO)Q1

Abstract

 One of the most important problems in research and applicable field of production management is a suitable scheduling for different operations. So, there are many approaches for job shop or non- JOB SHOP SCHEDULING PROBLEMs. Since JOB SHOP SCHEDULING PROBLEMs (JSP) belong to NP-Hard class, some met heuristics method such as Tabu Search, Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization are used in different papers. This paper tries to solve this problem by using these algorithms and compares their conclusions. So, some problems with different sizes are used and they are analyzed by time, quantified and parametric approaches.

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    APA: Copy

    SAMOUEI, PARVANEH, & FATTAHI, PARVIZ. (2017). AN ANALYTICAL AND COMPARATIVE APPROACH FOR USING METAHEURISTIC ALGORITHMS FOR JOB SHOP SCHEDULING PROBLEMS. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), 14(1 (52)), 63-76. SID. https://sid.ir/paper/164426/en

    Vancouver: Copy

    SAMOUEI PARVANEH, FATTAHI PARVIZ. AN ANALYTICAL AND COMPARATIVE APPROACH FOR USING METAHEURISTIC ALGORITHMS FOR JOB SHOP SCHEDULING PROBLEMS. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS)[Internet]. 2017;14(1 (52)):63-76. Available from: https://sid.ir/paper/164426/en

    IEEE: Copy

    PARVANEH SAMOUEI, and PARVIZ FATTAHI, “AN ANALYTICAL AND COMPARATIVE APPROACH FOR USING METAHEURISTIC ALGORITHMS FOR JOB SHOP SCHEDULING PROBLEMS,” JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), vol. 14, no. 1 (52), pp. 63–76, 2017, [Online]. Available: https://sid.ir/paper/164426/en

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