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.