ArticleScientific reports2025
Intelligent optimization method for hazardous materials transportation routing with multi-mode and multi-criterion collaborative constraints.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hazardous materials transportation route optimization problem is a pressing issue, and multi-dimensional evaluation criteria and diversified transportation modes complicate the problem. In response to this, a method for multi-mode transportation network and multi-criterion route optimization is proposed. Initially, A three-objective integer programming model is formulated, and an improved multi-objective genetic algorithm, termed DSNSGA3, is introduced to aid in decision-making. Specifically tailored to the problem's specifics, a chromosome encoding technique grounded in priority is devised to eliminate infeasible solutions. Subsequently, leveraging non-dominated sorting and crowding distance algorithms to assess the merit of multi-objective solutions, a local search strategy is introduced. This strategy serves dual purposes: it accelerates the algorithm's convergence rate and effectively minimizes the number of transshipments. Ultimately, an automatic weight-assigning decision-making method based on maximizing deviations is designed, culminating in a definitive decision-making plan. Numerical simulations reveal that the DSNSGA3, as designed in this paper, excels at identifying a diverse and widely distributed Pareto front. Compared to the traditional NSGA3, it demonstrates average improvements of 1.93% in solution accuracy, 1.32% in robustness, and a convergence advancement of 11.33 generations. The proposed decision-making method, based on Pareto solutions, adeptly balances various evaluation criteria, obtains a definitive solution, and provides a basis for multi-criteria intelligent decision-making in complex environments.
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