Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm

Abstract

For the optimal design of the sustainable supply chain network, considering the comprehensiveness of the problem factors, considering the three aspects of economy, environment and society, the goal is to minimize the establishment cost, minimize the emission of environ-mental pollution and maximize the number of labor. A mixed integer programming model is established to maximize the efficiency of the supply chain network. The innovation of this paper, first, is to consider the impact of economic, environmental and social benefits in a continuous supply chain, where the environmental benefits not only consider carbon emissions but also include the emissions of plant wastewater, waste and solid waste as influencing factors. Second, a multi-objective fuzzy affiliation function is constructed to measure the quality of the model solution in terms of the overall satisfaction value. Finally, the chaotic particle ant colony algorithm is proposed, and the problem of premature convergence in the operation of the particle swarm algorithm is solved. Experimental results show that the PSCACO algorithm proposed in this paper is compared with MOPSO, CACO and NSGA-II algorithms, and the convergence effect of the algorithm is concluded to be more effective to verify the effectiveness and feasibility of chaotic particle ant colony algorithm for solving multi-objective functions, which proposes a new feasible solution for the supply chain management.

R&D mode and coordination of green products in sustainable supply chain considering power structures

“…Feng et al [ 51 ] discussed the selection strategy of green product R&D in the chain-to-chain competition environment, and applied two-pricing contracts to realize the coordination of supply chain. It was found that whether the supply chain carried out green product R&D would be affected by the competitive supply chain selection strategy and the cost of green product R&D. Zhang et al [ 52 ] established a mixed integer programming model to study the optimal design of sustainable supply chain network, and put forward a chaotic particle-ant colony algorithm to solve multi-objective functions. Mohammadi et al [ 53 ] established a multi-objective mixed integer nonlinear programming model for the sustainable supply chain of perishable products with price-dependent demand and deterioration rate, determined the optimal pricing strategy and cycle length, and achieved profit maximization and specific social goals.…”