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

Orhan Engin; Cengiz Kahraman; Mustafa Kerim Yilmaz

doi:10.1007/978-3-642-02836-6_6

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

Department of Industrial Engineering

Selcuk University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

19 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 language	English
Title of host publication	Computational Intelligence in Flow Shop and Job Shop Scheduling
Editors	Uday Chakraborty
Pages	169-189
Number of pages	21
DOIs	https://doi.org/10.1007/978-3-642-02836-6_6
Publication status	Published - 2009

Publication series

Name	Studies in Computational Intelligence
Volume	230
ISSN (Print)	1860-949X

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1007/978-3-642-02836-6_6

Cite this

@inbook{f00a330576df40cd8a48fd8c8a158d12,

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

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).",

author = "Orhan Engin and Cengiz Kahraman and Yilmaz, \{Mustafa Kerim\}",

year = "2009",

doi = "10.1007/978-3-642-02836-6\_6",

language = "English",

isbn = "9783642028359",

series = "Studies in Computational Intelligence",

pages = "169--189",

editor = "Uday Chakraborty",

booktitle = "Computational Intelligence in Flow Shop and Job Shop Scheduling",

}

A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem: A real world application. / Engin, Orhan; Kahraman, Cengiz; Yilmaz, Mustafa Kerim.
Computational Intelligence in Flow Shop and Job Shop Scheduling. ed. / Uday Chakraborty. 2009. p. 169-189 (Studies in Computational Intelligence; Vol. 230).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - A scatter search method for multiobjective fuzzy permutation flow shop scheduling problem

T2 - A real world application

AU - Engin, Orhan

AU - Kahraman, Cengiz

AU - Yilmaz, Mustafa Kerim

PY - 2009

Y1 - 2009

N2 - 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).

AB - 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).

UR - https://www.scopus.com/pages/publications/78049281442

U2 - 10.1007/978-3-642-02836-6_6

DO - 10.1007/978-3-642-02836-6_6

M3 - Chapter

AN - SCOPUS:78049281442

SN - 9783642028359

T3 - Studies in Computational Intelligence

SP - 169

EP - 189

BT - Computational Intelligence in Flow Shop and Job Shop Scheduling

A2 - Chakraborty, Uday

ER -

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

Abstract

Publication series

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this