An ant colony system for permutation flow-shop sequencing [An article from: Computers and Operations Research]
Book Details
Author(s)K.-C. Ying, C.-J. Liao
PublisherElsevier
ISBN / ASINB000RR16XG
ISBN-13978B000RR16X3
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Computers and Operations Research, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Ant colony system (ACS) is a novel meta-heuristic inspired by the foraging behavior of real ant. This paper is the first to apply ACS for the n/m/P/C"m"a"x problem, an NP-hard sequencing problem which is used to find a processing order of n different jobs to be processed on m machines in the same sequence with minimizing the makespan. To verify the developed ACS algorithm, computational experiments are conducted on the well-known benchmark problem set of Taillard. The ACS algorithm is compared with other mata-heuristics such as genetic algorithm, simulated annealing, and neighborhood search from the literature. Computational results demonstrate that ACS is a more effective mata-heuristic for the n/m/P/C"m"a"x problem.
Description:
Ant colony system (ACS) is a novel meta-heuristic inspired by the foraging behavior of real ant. This paper is the first to apply ACS for the n/m/P/C"m"a"x problem, an NP-hard sequencing problem which is used to find a processing order of n different jobs to be processed on m machines in the same sequence with minimizing the makespan. To verify the developed ACS algorithm, computational experiments are conducted on the well-known benchmark problem set of Taillard. The ACS algorithm is compared with other mata-heuristics such as genetic algorithm, simulated annealing, and neighborhood search from the literature. Computational results demonstrate that ACS is a more effective mata-heuristic for the n/m/P/C"m"a"x problem.
