Reference group genetic algorithm for flexible job shop scheduling problem with multiple objective functions

Document Type : Research Paper

Authors

Industrial Engineering Department, Semnan University, Semnan, Iran

Abstract

This article studies flexible job-shop scheduling problem (FJSSP) considering three objective functions. The objectives are minimizing maximum completion time (Cmax), the maximum machine workload (Wmax), and the total workload (WT). After presenting the mathematical model of the problem, a genetic algorithm called Reference Group Genetic Algorithm(RGGA) is used to solve the problem. RGGA implements the reference group concept in the sociology to the genetic algorithm. The term " reference group" is credited to sociologist Robert K. Merton. Three standard data sets are used to evaluate the performance of RGGA. On the first data set, RGGA is compared to six algorithms in the literature, on the second data set RGGA is compared to four algorithms in the literature, and on the third data set RGGA is compared to three algorithms in the literature. Moreover, RGGA is compared with optimum solution in small size problem. Results show the superiority of RGGA in comparison to other algorithms.

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References

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Journal of Industrial and Systems Engineering
Volume 11, Issue 4 - Serial Number 4
November 2018
Pages 153-169

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History

  • Receive Date: 04 June 2018
  • Revise Date: 30 October 2018
  • Accept Date: 28 October 2018

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