Bicriterion Optimization for Flow Shop with a Learning Effect Subject to Release Dates

This paper investigates a two-machine flow shop problem with release dates in which the job processing times are variable according to a learning effect. The bicriterion is to minimize the weighted sum of makespan and total completion time subject to release dates. We develop a branch-and-bound (B&a...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2018; no. 2018; pp. 1 - 12
Main Authors Wang, Ji-Bo, Yang, Jing, Xu, Jian
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
Hindawi
John Wiley & Sons, Inc
Wiley
Subjects
Algorithms
Completion time
Job shops
Lower bounds
Production scheduling
Sequential scheduling
Upper bounds
Online AccessGet full text
ISSN1076-2787
1099-0526
DOI10.1155/2018/9149510

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Summary:This paper investigates a two-machine flow shop problem with release dates in which the job processing times are variable according to a learning effect. The bicriterion is to minimize the weighted sum of makespan and total completion time subject to release dates. We develop a branch-and-bound (B&B) algorithm to solve the problem by using a dominance property, several lower bounds, and an upper bound to speed up the elimination process of the search tree. We further propose a multiobjective memetic algorithm (MOMA), enhanced by an initialization strategy and a global search strategy, to obtain the Pareto front of the problem. Computational experiments are also carried out to examine the effectiveness and the efficiency of the B&B algorithm and the MOMA algorithm.
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ISSN:1076-2787
1099-0526
DOI:10.1155/2018/9149510