Title of article :
Mathematical modelling of a decentralized multi-echelon supply chain network considering service level under uncertainty
Author/Authors :
Nourifar, R. Department of Industrial Engineering - Mazandaran University of Science and Technology, Babol, Iran , Mahdavi, I. Department of Industrial Engineering - Mazandaran University of Science and Technology, Babol, Iran , Mahdavi-Amiri, N. Department of Mathematical Sciences - Sharif University of Technology, Tehran, Iran , Paydar, M.M. Department of Industrial Engineering - Babol Noshirvani University of Technology, Babol, Iran
Pages :
21
From page :
1634
To page :
1654
Abstract :
We study a multi-time, multi-product and multi-echelon supply chain aggregate procurement, production and distribution planning problem and discuss the implications of formulating a tri-level model to integrate procurement, production and distribution, maintaining the existing hierarchy in the decision process. In our model, there are three different decision makers controlling the procurement, production and the distribution processes in the absence of cooperation because of different optimization strategies. First, we present a hierarchical tri-level programming model to deal with decentralized supply chain problems. Then, an algorithm is presented to solve the proposed model. A numerical illustration is provided to show the applicability of the optimization model and the proposed algorithm. In order to evaluate the application of the model and the proposed algorithm, ten sets of small and large problems are randomly generated and tested. The experimental results show that our proposed fuzzy-stochastic simulation based hierarchical interactive particle swarm optimization (Sim-HIPSO) performs well in finding good approximate solutions within reasonable computation times.
Keywords :
Decentralized decision making , supply chain network , uncertainty , tri-level , programming , service level
Journal title :
Scientia Iranica(Transactions E: Industrial Engineering)
Serial Year :
2020
Record number :
2629156
Link To Document :
بازگشت