A genetic algorithm approach for multi-objective optimization of supply chain networks
Küçük Resim Yok
Tarih
2006
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
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. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms to find the set of Pareto-optimal solutions for multi-objective SCN design problem. To deal with multi-objective and enable the decision maker for evaluating a greater number of alternative solutions, two different weight approaches are implemented in the proposed solution procedure. An experimental study using actual data from a company, which is a producer of plastic products in Turkey, is carried out into two stages. While the effects of weight approaches on the performance of proposed solution procedure are investigated in the first stage, the proposed solution procedure and simulated annealing are compared according to quality of Pareto-optimal solutions in the second stage. © 2006 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Genetic algorithm, Multi-objective optimization, Supply chain network
Kaynak
Computers and Industrial Engineering
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
51
Sayı
1
