Multi-objective Optimization Modelling and Solution for Urban Hazardous Wastes Transportation Network
To reduce the hazardous wastes transportation risk and improve the network efficiency,a multi-objective optimization modelling and solution for urban hazardous wastes transportation was proposed.It aimed at solving the combinatorial optimization problems(i.e.,transport facility location,heterogeneous vehicle acquisition and network design)for multi-category hazardous wastes.Considering the impact of emergency response time on public perception,the proposed perceived risk measurement model was formulated.The multi-objective optimization model,with minimum cost and perceived risk,was developed by using the two-commodity flow formulation.According to the model's complexity,the three-stage hybrid multi-objective algorithm,based on the Multi-objective Evolutionary Algorithm Based on Decomposition(MOEA/D)&branch-and-cut,was designed.Finally,a case study in Kunming city and several tests were provided to demonstrate the workability of proposed network optimization model and the three-stage algorithm.The result indicates that the proposed model and algorithm can provide multiple efficient schemes within 1 177.8 s for decision makers.Compared with the original scheme,the proposed scheme can provide the reduction of 53.58%and 30.56%in transportation cost and transportation risk respectively.The proposed model and algorithm are sensitive to the vehicle maximum load,facility capacity,and emergency response time.Compared with the traditional models,the proposed risk assessment model can reduce the transportation cost by 10.20%.The proposed network optimization model can effectively reduce the computation,and improve the optimization rate of optimal solution.It can reduce the gap between the result and the optimal solution by 5.22%.The proposed method can reduce the computational time by 67.28%,and keep the relatively high stable performance in solving different scaled problems.
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