Developing a Stackelberg security game for circular supply chain network

The purpose of this study is to develop a bilevel problem for interdiction and protection of circular supply chain network (BPIPCSCN) for an Indian manufacturing organization. This work used a bilevel mixed-integer quadratic programming approach for the analysis of interdiction and fortification operations in circular production systems and the corresponding economic and environmental conditions. A Stackelberg leadership model between a network planner (defender) and an interdictor (attacker) is studied for evaluating the economic and environmental benefits. The defender selects which of the suppliers, repair and collection centers and sales and distribution centers to protect simultaneously, for maximizing monetary benefit and minimizing environmental impact. Furthermore, the attacker chooses which of them to interdict and disturb the operation of a circular supply chain network such that the monetary benefit is minimized and environmental impact is maximized. This work shows the performance of a circular economy structure in supply chain sustainability in the presence of interdiction and protection operations. The dataset gathered from the case organization is applied. The CPLEX Optimizer solver for MATLAB is executed to simulate the new mathematical model. Due to non-deterministic polynomial time (NP)-hardness of the BPIPCSCN, a powerful tabu search was developed to solve the new problem. A real-world case study of circular supply chain network for an Indian manufacturing organization is considered to declare the application of the novel mathematical problem and the validity of the proposed method. The model is able to calculate the economic profit and environmental impacts obtained through circular operations with respect to the defender's decisions and attacks on suppliers, repair and collection centers and sales and distribution centers. The flow of various levels through the network is also achieved. The proposed tabu search and two comparative metaheuristic algorithms are tested on 36 instances. The computational results demonstrate that the new strategy of tabu search really improves the solution quality, and it is a competitive approach to the considered problem.