Multi-Objective Cold Chain Distribution Based on Dual-Mode Updated Five-Element Cycle Algorithm

With the development of the logistics industry, cold chain logistics, as an important branch of the logistics industry, have been receiving more and more attention. The waste of resources in cold chain logistics and distribution is a problem that cannot be underestimated. It is a promising strategy for reducing resource waste via solving the multi-objective optimization model to provide an effective distribution plan. To this end, this paper establishes a multi-objective cold chain logistics optimization model with minimizing distribution costs and maximizing customer satisfaction as the objective function. Customer satisfaction is reflected via the relationship between the delivery vehicle’s arrival time at the customer’s point and the customer’s specific time window. Delivery costs are composed of transportation costs, cargo damage costs, cooling costs, and time penalty costs. We propose a five-element cycle optimization (FECO) algorithm with dual-mode updating individuals (FECO-DMUI) to solve the multi-objective cold chain logistics optimization model. By comparing with FECO algorithm, NSGA-II, whale optimization algorithm and gray wolf optimization algorithm, the proposed model and FECO-DMUI algorithm is effectively verified through specific examples. Meanwhile, it is shown that FECO-DMUI algorithm can obtain the optimal solution set of path optimization more efficiently in the multi-objective cold chain distribution problem.