A hybrid genetic algorithm for production and distribution
Felix T. S. Chan,
S. H. Chung and
Subhash Wadhwa
Omega, 2005, vol. 33, issue 4, 345-355
Abstract:
This paper develops a hybrid genetic algorithm for production and distribution problems in multi-factory supply chain models. Supply chain problems usually may involve multi-criterion decision-making, for example operating cost, service level, resources utilization, etc. These criteria are numerous and interrelated. To organize them, analytic hierarchy process (AHP) will be utilized. It provides a systematic approach for decision makers to assign weightings and relate them. Meanwhile, genetic algorithms (GAs) will be utilized to determine jobs allocation into suitable production plants. Genetic operators adopted to improve the genetic search algorithm will be introduced and discussed. Finally, a hypothetical production-distribution problem will be solved by the proposed algorithm. The optimization results show that it is reliable and robust.
Keywords: Genetic; algorithms; Analytic; hierarchy; process; Multi-factory; Multi-criterion (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305-0483(04)00089-1
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:33:y:2005:i:4:p:345-355
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Omega is currently edited by B. Lev
More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().