A Mathematical Model and Solution for Cost-Driven Job-Shop Scheduling Problem Computer Science for Environmental Engineering and EcoInformatics
K. Sun, G. Yang, and J. Bai. volume 159 of Communications in Computer and Information Science, chapter 73, Springer Berlin Heidelberg, Berlin, Heidelberg, (2011)
DOI: 10.1007/978-3-642-22691-5\_73
Abstract
This paper presents a cost-driven model of the job-shop scheduling problem and an effective hybrid optimization algorithm to solve it. The cost model is developed in terms of a combination of multi-dimensional costs generated from product transitions, revenue loss, earliness / tardiness penalty, and so on. The new hybrid optimization algorithm combines the strong global search ability of scatter search with the strong local search ability of simulated annealing. In order to illustrate the effectiveness of the hybrid method, several test problems are generated, and the performance of the proposed method is compared with other evolutionary algorithms. The experimental simulation tests show that the hybrid method is quite effective at solving the cost-driven job-shop scheduling problem.
%0 Book Section
%1 citeulike:10361251
%A Sun, Kai
%A Yang, Gen-ke
%A Bai, Jie
%B Communications in Computer and Information Science
%C Berlin, Heidelberg
%D 2011
%E Yu, Yuanxu
%E Yu, Zhengtao
%E Zhao, Jingying
%I Springer Berlin Heidelberg
%K imported
%P 418--423
%R 10.1007/978-3-642-22691-5\_73
%T A Mathematical Model and Solution for Cost-Driven Job-Shop Scheduling Problem Computer Science for Environmental Engineering and EcoInformatics
%U http://dx.doi.org/10.1007/978-3-642-22691-5\_73
%V 159
%X This paper presents a cost-driven model of the job-shop scheduling problem and an effective hybrid optimization algorithm to solve it. The cost model is developed in terms of a combination of multi-dimensional costs generated from product transitions, revenue loss, earliness / tardiness penalty, and so on. The new hybrid optimization algorithm combines the strong global search ability of scatter search with the strong local search ability of simulated annealing. In order to illustrate the effectiveness of the hybrid method, several test problems are generated, and the performance of the proposed method is compared with other evolutionary algorithms. The experimental simulation tests show that the hybrid method is quite effective at solving the cost-driven job-shop scheduling problem.
%& 73
%@ 978-3-642-22690-8
@incollection{citeulike:10361251,
abstract = {{This paper presents a cost-driven model of the job-shop scheduling problem and an effective hybrid optimization algorithm to solve it. The cost model is developed in terms of a combination of multi-dimensional costs generated from product transitions, revenue loss, earliness / tardiness penalty, and so on. The new hybrid optimization algorithm combines the strong global search ability of scatter search with the strong local search ability of simulated annealing. In order to illustrate the effectiveness of the hybrid method, several test problems are generated, and the performance of the proposed method is compared with other evolutionary algorithms. The experimental simulation tests show that the hybrid method is quite effective at solving the cost-driven job-shop scheduling problem.}},
added-at = {2012-03-02T03:39:18.000+0100},
address = {Berlin, Heidelberg},
author = {Sun, Kai and Yang, Gen-ke and Bai, Jie},
biburl = {https://www.bibsonomy.org/bibtex/2ad606d8fb5ddff0ca1c9343443b7d3f0/baby9992006},
chapter = 73,
citeulike-article-id = {10361251},
citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-22691-5\_73},
citeulike-linkout-1 = {http://www.springerlink.com/content/r65843tp01853570},
doi = {10.1007/978-3-642-22691-5\_73},
editor = {Yu, Yuanxu and Yu, Zhengtao and Zhao, Jingying},
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isbn = {978-3-642-22690-8},
keywords = {imported},
pages = {418--423},
posted-at = {2012-02-17 09:47:47},
priority = {2},
publisher = {Springer Berlin Heidelberg},
series = {Communications in Computer and Information Science},
timestamp = {2012-03-02T03:39:22.000+0100},
title = {{A Mathematical Model and Solution for Cost-Driven Job-Shop Scheduling Problem Computer Science for Environmental Engineering and EcoInformatics}},
url = {http://dx.doi.org/10.1007/978-3-642-22691-5\_73},
volume = 159,
year = 2011
}