Location Selection Formula of Logistics Distribution Center Research Based on Immune Genetic Algorithm
Logistics Distribution Center (LDC) is the key of the logistics system. Location selection of LDC is a basic step of logistics system planning. Optimization location selection of LDC ensures logistics system operation is efficient. Currently, a large number of optimization algorithm apply in location Selection of LDC, but in general the ability of overall situation search of these optimization algorithm are not very powerful and these are not very easy to obtain the optimal solution. Immune Genetic Algorithm (IGA) is a new type of optimization algorithm that has combined the immune operator which is from Artificial immune theory. It has the ability that can efficiently avoid premature convergence, moreover it has more chance to obtain the optimal solution of overall situation. This paper will introduce the IGA to resolve the location selection of LDC, propose a location selection formula of LDC based on IGA, and by the example analysis, it will show that IGA in LDC location problems of the application of effectiveness.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411841
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Supplemental Notes:
- Copyright © 2011 ASCE
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Du, Yibo
- Wang, Rui
- Si, Wei
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Conference:
- Third International Conference on Transportation Engineering (ICTE)
- Location: Chengdu , China
- Date: 2011-7-23 to 2011-7-25
- Publication Date: 2011
Language
- English
Media Info
- Media Type: Digital/other
- Features: References;
- Pagination: pp 2382-2387
- Monograph Title: ICTE 2011
Subject/Index Terms
- TRT Terms: Algorithms; Fuzzy sets; Location; Logistics; Supply chain management
- Uncontrolled Terms: Distribution centers
- Subject Areas: Design; Freight Transportation; Terminals and Facilities; I20: Design and Planning of Transport Infrastructure;
Filing Info
- Accession Number: 01447184
- Record Type: Publication
- ISBN: 9780784411841
- Files: TRIS, ASCE
- Created Date: Sep 25 2012 9:24AM