A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application

Orhan Engin*, Cengiz Kahraman, Mustafa Kerim Yilmaz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

18 Citations (Scopus)

Abstract

In this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).

Original languageEnglish
Title of host publicationComputational Intelligence in Flow Shop and Job Shop Scheduling
EditorsUday Chakraborty
Pages169-189
Number of pages21
DOIs
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence
Volume230
ISSN (Print)1860-949X

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