Sustainable closed-loop supply chain network planning considering price competition using particle chaotic ant colony algorithm

Considering the impact of environmental pollution and market competition on the business model of enterprises, a method of constructing sustainable supply chain network model under the price competition environment is proposed to achieve the balance of economic benefit, ecological benefit, environmental benefit and social benefit. Firstly, based on the concepts of sustainability and price competition, the model with maximum total network profit, minimum carbon emission and maximum social benefit is designed. Secondly, based on fuzzy programming theory, an expected value fuzzy chance constrained programming model with confidence measure is constructed to address the challenge of designing a sustainable closed-loop supply chain network in the face of uncertain conditions. Thirdly, the problems of premature convergence and slow convergence during the traditional particle swarm optimization algorithm and genetic algorithm are solved with the particle chaotic ant colony algorithm (PSCACO). Finally, taking a manufacturing enterprise as an example. By analyzing the different confidence level measures under single objective optimization and multi-objective optimization, sustainable closed-loop supply chain network planning method established is verified on feasibility and effectiveness.