a solution approach for optimizing a closed-loop supply chain network based on circular economy: an application of nsga-ii algorithm

In response to increasing attention to the circular economy, supply chain network design is an effective approach in which firms can integrate and allocate resources and improve their overall performance. this paper presents a multi-objective mathematical model for a multi-echelon multi-product multi-period closed-loop supply chain network, focusing on the circular economy concept. gams software is used to find an optimal solution for a small-size problem. however, this problem in large dimensions is included in the class of complex problems known as np-hard, where obtaining the solution using the exact methods will be very time-consuming and sometimes impossible. therefore, the specific development of this study is to present an application of the nsga-ii algorithm to solve the proposed model on a large scale. some examples of small, medium and large problems are solved in 20 and 100 iterations. then sensitivity analysis and pareto diagram are presented. a comparison of the results obtained from the nsga-ii algorithm with the exact solution method for small-sized problems confirms the effectiveness of the proposed method for solving large-scale complex problems. taking environmental and social impacts, as well as economic objectives into account, the results of this paper assist decision-makers in designing their circular supply chain network. also, the general results of the research are practical for managers who intend to move towards a circular economy, reduce costs, and increase productivity and efficiency.

a solution approach for optimizing a closed-loop supply chain network based on circular economy: an application of nsga-ii algorithm

in response to increasing attention to the circular economy, supply chain network design is an effective approach in which firms can integrate and allocate resources and improve their overall performance. this paper presents a multi-objective mathematical model for a multi-echelon multi-product multi-period closed-loop supply chain network, focusing on the circular economy concept. gams software is used to find an optimal solution for a small-size problem. however, this problem in large dimensions is included in the class of complex problems known as np-hard, where obtaining the solution using the exact methods will be very time-consuming and sometimes impossible. therefore, the specific development of this study is to present an application of the nsga-ii algorithm to solve the proposed model on a large scale. some examples of small, medium and large problems are solved in 20 and 100 iterations. then sensitivity analysis and pareto diagram are presented. a comparison of the results obtained from the nsga-ii algorithm with the exact solution method for small-sized problems confirms the effectiveness of the proposed method for solving large-scale complex problems. taking environmental and social impacts, as well as economic objectives into account, the results of this paper assist decision-makers in designing their circular supply chain network. also, the general results of the research are practical for managers who intend to move towards a circular economy, reduce costs, and increase productivity and efficiency.