A Green Closed-loop Supply Chain with Allocating ‎Retailer to Probabilistic Customers by Considering ‎Electric Converter of CO2 to O2 in Vehicles

In this paper, a closed-loop supply chain is modeled to obtain the best allocation and location of retailers including production centers, retailers' centers, probabilistic customers, collection and disposal centers. In this study, by considering electric conversion of CO2 to O2 in vehicles, the amount of environmental pollution is minimized. Furthermore, two strategies are considered to find the best places for retailers by focusing on: 1- the type of expected movement (Rectangular, Euclidean, Euclidean Square, and Chebyshev); 2- expected coverage (distance and time). To this end, a bi-objective nonlinear programming model is proposed. This model concurrently compares strategies 1 and 2 and selects the best competitor. Based on the selected strategy, the best allocation is made by employing a heuristic algorithm and the locations of the best retailers are determined. As the proposed model is NP-hard in its nature of the problem, a meta-heuristic, namely, a non-dominated sorting genetic algorithm is employed for the solution process. Eventually, to authenticate and confirm the effectiveness of the suggested model, a numerical example is given and solved utilizing optimization software, and the results are analyzed.