teaching learning based optimization

In Iran, Although the PET recycling industry is new, due to the appropriate economic return, many individuals and companies have turned to this industry. Creating a proper structure in the distribution and collection network of these products can provide a good base to replace its consumption with more environmentally friendly products. This paper aims to present a mixed integer linear programming (MILP) model for designing a supply chain network in which customer demand is dependent on the price offered by distribution centers. The proposed model addresses two main global trends in this industry: 1- Economizing the collection and recycling of bottles, 2- Price sensitivity analysis on demand for PET bottles. In addition, we applied a recently developed optimization algorithm (TLBO) to this problem with significant modifications. Since the standard version of TLBO is introduced for continuous representation methods and the representation method used in this paper (priority-based encoding) is and discrete method, modifications have been made to convert this method to a continuous one. Finally, the performance of this algorithm is assessed in terms of the quality of answers and the convergence speed and compared with two other meta-heuristic algorithms.