不确定需求下的危险废物混合储运协同优化

    Collaborative Optimization of Hazardous Waste Mixed Storage and Transportation under Uncertain Demands

    • 摘要: 为降低危险废物混合储运的风险和成本,提出一类考虑需求不确定的危险废物混合储运多目标优化建模与求解问题,旨在协同优化设施选址、堆存量控制和路线设计决策。考虑多类危险废物混合存储的危害性,引入毒性系数和恶臭因子构建处理站的环境影响负效用函数;考虑中转站的居民负效用影响,设计危险废物混合存储风险的度量方法。根据储运需求的不确定性,以分布函数拟合危险废物产量,并计算设施的最大堆存量。以总风险最小和总成本最小为优化目标,构建危险废物混合储运的选址−选线模型。根据模型的计算复杂度以及多目标特征,设计改进NSGA-II算法的模型求解步骤。通过多个测试算例验证模型和算法的有效性。计算结果表明,新模型和算法能够提供多个有效的选址−选线方案;相较于传统的风险模型,新建的风险模型能够提供成本和风险均摊度更优的方案,实现人员安全和环境卫生的协同保障;相较于常规的多目标优化方法,新算法能够缩短38.79%的求解时间,并能在1700 s以内求解不同规模的优化问题,且保持较高的计算稳定性。

       

      Abstract: To reduce the total risk and cost related to the hazardous wastes mixed storage and transportation, a multi-objective optimization under uncertain demands is proposed, which aims to simultaneously decide facility location, inventory control and route design. Considering the risk derived from mixed storage, an environmental impact disutility function of the treatment station is formulated by introducing toxicity coefficient and odor factor. The resident disutility effect of transfer stations is considered to develop the corresponding risk assessment model. Considering the uncertain demand of hazardous waste inventory and transportation, a computation method of total generation amount is formulated according to the distribution function, and computing the standard line of facility inventory. Minimizing the total risk and cost, a location and transportation model for the hazardous wastes mixed storage and transportation is developed. Based on the improved NSGA-II algorithm, the solution procedure is designed according to the complexity and characteristics of the proposed model. Finally, several tests are provided to demonstrate the workability of the proposed model and algorithm. In which, the computational results show that, the new model and algorithm can provide multiple efficient plans. Comparing to the traditional risk model, the integrated assessment can provide a more economical plan of with great performance in risk equity, which achieving the cooperative guarantee of personnel safety and environmental protection. Comparing to general multi-objective optimization methods, the improved algorithm can shorten the computational time by at least 38.79%, and provide optimal plan within 1700 seconds as well as keep stable performance in solving the problems of different scales

       

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