A hybrid GA-TLBO Algorithm for Optimizing a Capacitated Three-Stage Supply Chain Network

A teaching-learning-based optimization (TLBO) algorithm is a new population-based algorithm applied to some applications in the literature successfully. In this paper, a hybrid genetic algorithm (GA)-TLBO algorithm is proposed for the capacitated three-stage supply chain network design (SCND) problem. To escape infeasible solutions emerged in the problem of interest due to realistic constraints, a combination of a random key and priority-base encoding scheme is proposed. To assess the quality of the proposed hybrid GA-TLBO algorithm, some numerical examples are conducted. Then, the results are compared with those of GA, TLBO and exact algorithms.

Keywords:

Supply chain network design , Teaching-learning-based optimization , Genetic algorithm , Priority-base encoding