A hybrid GA-TLBO algorithm for optimizing a capacitated three-stage supply chain network

International Journal of Industrial Engineering and Production Research

Reza Tavakkoli-Moghaddam¹  Reza Babazadeh² 

[1] University of Tehran;Urmia University;

关键词: Supply chain network design;    Teaching learning-based optimization;    Genetic algorithm;    Priority-base encoding.;   

DOI  :  

来源: DOAJ

【 摘 要 】

A teaching-learning-based optimization (TLBO) algorithm is a new population-based algorithm applied in some applications in the literature successfully. Moreover, a genetic algorithm (GA) is a popular tool employed widely in many disciplines of engineering. In this paper, a hybrid GA-TLBO algorithm is proposed for the capacitated three-stage supply chain network design (SCND) problem. The SCND problem as a strategic level decision-making problem in supply chain management is an NP-hard class of computational complexity. To escape infeasible solutions emerged in the problem of interest due to realistic constraints, combination of a random key and priority-base encoding scheme is also used. To assess the quality of the proposed hybrid GA-TLBO algorithm, some numerical examples are conducted. Then, the results are compared with the GA, TLBO, differential evolution (DE) and branch-and -bound algorithms. Finally, the conclusion is provided.

【 授权许可】

Unknown