MULTI-OBJECTIVE PRODUCTION NETWORK SCHEDULING USING SUB-POPULATION GENETIC ALGORITHM AND ELASTIC METHOD

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BEHNAMIAN J.

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Paper Information

Journal: JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH IN PRODUCTION SYSTEMS (IERPS) Year:2016 | Volume:3 | Issue:6 Page(s): 133-147

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Title

MULTI-OBJECTIVE PRODUCTION NETWORK SCHEDULING USING SUB-POPULATION GENETIC ALGORITHM AND ELASTIC METHOD

Author(s)

BEHNAMIAN J. | Issue Writer Certificate

Keywords

MULTI-OBJECTIVE SCHEDULINGQ2

MULTI-FACTORY PRODUCTIONQ2

ELASTIC METHODQ2

SUB-POPULATION GENETIC ALGORITHMQ2

Abstract

Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran. The globalization trend causes the emergence of intense competition among manufacturers to gain more profits. In order to be competitive in today’s rapidly changing business world, organizations have shifted from a centralized single factory production to a decentralized multi-factory structure. We assume that production takes place in several factories, which may be geographically distributed in different locations, in order to comply with and to take advantage from the trend of globalization. This allows them to be closer to their customers, to employ professionals, to comply with local laws, to focus on a few product types, to produce and market their products more effectively, and respond to market changes more quickly. These can be attained by transporting the jobs from an overloaded factory to the factory which has fewer workloads. Obviously, considering these assumptions, as well as MULTI-OBJECTIVE SCHEDULING are surely more practical than those scheduling problems which do not take them into account. In this research, after formulating the scheduling problem as a mixed integer linear programming for simultaneous minimization of the sum of the earliness and tardiness of jobs and the total completion time, a new exact method and a multi-objective metaheuristic algorithm are proposed. Finally, the heuristic algorithm and the output of particle swarm-based algorithm are reported.

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APA: Copy

BEHNAMIAN, J.. (2016). MULTI-OBJECTIVE PRODUCTION NETWORK SCHEDULING USING SUB-POPULATION GENETIC ALGORITHM AND ELASTIC METHOD. JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH IN PRODUCTION SYSTEMS (IERPS), 3(6), 133-147. SID. https://sid.ir/paper/241311/en

Vancouver: Copy

BEHNAMIAN J.. MULTI-OBJECTIVE PRODUCTION NETWORK SCHEDULING USING SUB-POPULATION GENETIC ALGORITHM AND ELASTIC METHOD. JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH IN PRODUCTION SYSTEMS (IERPS)[Internet]. 2016;3(6):133-147. Available from: https://sid.ir/paper/241311/en

IEEE: Copy

J. BEHNAMIAN, “MULTI-OBJECTIVE PRODUCTION NETWORK SCHEDULING USING SUB-POPULATION GENETIC ALGORITHM AND ELASTIC METHOD,” JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH IN PRODUCTION SYSTEMS (IERPS), vol. 3, no. 6, pp. 133–147, 2016, [Online]. Available: https://sid.ir/paper/241311/en

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