Optimization method of low-carbon logistics network for automotive-parts based on IPSO

We propose a low-carbon automotive-component logistics network optimization method based on the improved particle swarm algorithm (IPSO) to reduce delivery times and operational costs while lowering carbon footprints. Accounting for key variables such as transportation distance, load capacity and transport modes, a multi-objective optimization model of the cost-optimal green automotive-parts logistics network is established and grouping-control evolution strategy, opposition-based search and mutation-crossover strategies are introduced in particle swarm algorithm (PSO) to obtain a global optimal solution. Experimental results show that the proposed low-carbon logistics optimization network achieves lower costs, times and carbon emissions compared to the traditional networks.