A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system

This paper presents a bi-objective optimization model for designing a closed loop supply chain (CLSC) network under uncertainty in which the total costs and the maximum waiting times in the queue of products are considered to minimize. A general multi-priority and multi-server queuing system for parallel processing execution is proposed. Also a new hybrid solution approach is introduced based on interval programming, stochastic programming, robust optimization approach, and fuzzy multi-objective programming. Furthermore, a meta-heuristic algorithm called self-adaptive imperialist competitive algorithm (SAICA) is put forward for the given problem. Then, in order to evaluate the quality of the solutions obtained by this algorithm, a lower bound procedure is investigated. Finally, various computational experiments are carried out to assess the proposed model and solution approaches.