Bicriterion optimization for flow shop with a learning effect subject to release dates
type: Item
instance of: scholarly article
title: Bicriterion optimization for flow shop with a learning effect subject to release dates
zbMATH Open document ID: 1407.90178
DOI: 10.1155/2018/9149510
author: Ji-Bo Wang
author: Jian Xu
author: Jing Yang
published in: Complexity
publication date: 2019-02-19T00:00:00Z
review text: 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.
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C29
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7024928
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/9149510
OpenAlex ID: W2897747641
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Wikidata QID: Q129084637
description: scientific article; zbMATH DE number 7024928