A steady-state genetic algorithm for multi-product supply chain network design
Küçük Resim Yok
Tarih
2009
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
PERGAMON-ELSEVIER SCIENCE LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management (SCM). The problem is often an important and strategic operations management problem in SCM. The design task involves the choice of facilities (plants and distribution centers (DCs)) to be opened and the distribution network design to satisfy the customer demand with minimum cost. This paper presents it solution procedure based on steady-state genetic algorithms (ssGA) with it new encoding structure for the design of a single-source, multi-product, multi-stage SCN. The effectiveness of the ssGA has been investigated by comparing its results with those obtained by CPLEX, Lagrangean heuristic, hyrid GA and simulated annealing on a set of SCN design problems with different sizes. (C) 2007 Elsevier Ltd. All rights reserved.
Açıklama
35th International Conference on Computers and Industrial Engineering -- JUN 19-22, 2005-2006 -- Istanbul, TURKEY
Anahtar Kelimeler
Supply chain network design, Genetic algorithms, Simulated annealing, Lagrangean heuristic
Kaynak
COMPUTERS & INDUSTRIAL ENGINEERING
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
56
Sayı
2
