Routing optimization for urban diffusible chemicals distribution considering the impact of response times with potential blockages and rescue teams capabilities

Appropriate transportation management significantly influences both operational costs and associated risks of diffusible chemicals distribution. Urban diffusible chemicals distribution differs distinctly from conventional distributions, presenting significant challenges for routing arrangement. This study investigates urban diffusible chemicals distribution, proposing a routing optimization model that incorporates urban rescue team points while accounting for response times with potential blockages, rescue team capabilities, and their impact on routing decision-making. A composite solution method is proposed, encompassing model pre-processing techniques and a two-stage solution framework. In Stage I, an Improved Non-dominated Sorting Genetic Algorithm-II (Improved NSGA-II) is conducted to generate the Pareto frontier; and in Stage II, a post-processing procedure is implemented to facilitate the decision-maker's selection of appropriate solutions. The method is tested by computational experiments, the results show that the Improved NSGA-II can enhance the Hypervolume by up to 20.20% (average 6.99%). Finally, sensitivity analysis on the population and crossover probability related parameters is reported. Furthermore, several insights governing the cost and risk of diffusible chemicals distribution are concluded, including selecting routes with densely distributed RT points and prioritizing regions where RT points maintain substantial rescue capabilities.