AN EFFICIENT ALGORITHM FOR SOLVING DI-OBJECTIVE FUZZY JOB-SHOP SCHEDULING PROBLEMS BY GENETIC ALGORITHMS AND DATA MINING

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RABANI M.; TAVAKOLI MOGHADAM R.; RANJBAR M.

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Journal: AMIRKABIR Year:2004 | Volume:15 | Issue:58-D Page(s): 570-591

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Title

AN EFFICIENT ALGORITHM FOR SOLVING DI-OBJECTIVE FUZZY JOB-SHOP SCHEDULING PROBLEMS BY GENETIC ALGORITHMS AND DATA MINING

Author(s)

RABANI M. | TAVAKOLI MOGHADAM R. | RANJBAR M. | Issue Writer Certificate

Keywords

GENETIC ALGORITHMSQ4

JOBSHOP PROBLEMQ2

DATA MININGQ4

FUZZY JOBSHOP SHEDULINGQ4

Abstract

This paper presents a meta-heuristic algorithm for solving bi-objective fuzzy job shop scheduling problems. These objectives are to minimize the makes pan and minimize the early and late penalty. Processing time and due date are considered as fuzzy triangular numbers. This paper also introduces a novel use of DATA MINING algorithm for solving of combinatorial optimization problems. The proposed algorithm combines GENETIC ALGORITHMS and an attribute-oriented induction algorithm, which is much quicker than previous methods providing the optimal solution. By, considering the structure of proposed algorithm, the whole feasible solutions of a special job shop-scheduling problem are considered as a database. Attribute-oriented induction algorithm must find similar relationships and latent patterns among this database. This algorithm helps GENETIC ALGORITHMS to find the optimal or near-optimal solution much quicker than previous methods. Due to genetic inheritance in solutions obtained by GENETIC ALGORITHMS, the next generation has more similar relationships between their characteristics, operations and sequences. In this paper, three test problems are conducted in order to compare with other solutions reported in the literature and to show the efficiency of the proposed algorithm.

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APA: Copy

RABANI, M., TAVAKOLI MOGHADAM, R., & RANJBAR, M.. (2004). AN EFFICIENT ALGORITHM FOR SOLVING DI-OBJECTIVE FUZZY JOB-SHOP SCHEDULING PROBLEMS BY GENETIC ALGORITHMS AND DATA MINING. AMIRKABIR, 15(58-D), 570-591. SID. https://sid.ir/paper/847/en

Vancouver: Copy

RABANI M., TAVAKOLI MOGHADAM R., RANJBAR M.. AN EFFICIENT ALGORITHM FOR SOLVING DI-OBJECTIVE FUZZY JOB-SHOP SCHEDULING PROBLEMS BY GENETIC ALGORITHMS AND DATA MINING. AMIRKABIR[Internet]. 2004;15(58-D):570-591. Available from: https://sid.ir/paper/847/en

IEEE: Copy

M. RABANI, R. TAVAKOLI MOGHADAM, and M. RANJBAR, “AN EFFICIENT ALGORITHM FOR SOLVING DI-OBJECTIVE FUZZY JOB-SHOP SCHEDULING PROBLEMS BY GENETIC ALGORITHMS AND DATA MINING,” AMIRKABIR, vol. 15, no. 58-D, pp. 570–591, 2004, [Online]. Available: https://sid.ir/paper/847/en

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