Publication:
Hybrid flow-shop: a memetic algorithm using constraint-based scheduling for efficient search

Placeholder

School / College / Institute

Program

KU-Authors

KU Authors

Co-Authors

Sevaux, Marc
Jouglet, Antoine

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as the local search engine of the memetic algorithm. Next, we present the new memetic algorithm. We lastly explain the computational experiments carried out to evaluate the performance of three algorithms (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm) in terms of both the quality of the solutions produced and the efficiency. These results demonstrate that the memetic algorithm produces better quality solutions and that it is very efficient.

Source

Publisher

Springer Nature

Subject

Industrial engineering

Citation

Has Part

Source

Journal of Mathematical Modelling and Algorithms

Book Series Title

Edition

DOI

10.1007/s10852-008-9101-1

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads

View PlumX Details