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An Improved Multi-Objective Programming with Augmented ε -Constraint Method for Hazardous Waste Location-Routing Problems

机译:一种改进的多目标规划,具有增强ε-concraint方法的危险废物位置路由问题

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Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε -constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
机译:由于附近居民和环境的潜在风险,危险的废物位置路由问题具有重要性。在本文中,基于多目标混合整数编程方法开发了一种改进的数学制构。该型号旨在协助决策者选择不同设施的地点,包括治疗厂,回收植物和处置场所,为危险废物处理提供适当的技术,以及路由运输。在该模型中,考虑了两个关键因素:系统运营成本和当地居民施加的风险,并将赔偿因子引入风险目标职能,以便考虑到一种危险风险水平的事实废物或处理技术可能会因其他类型而显着不同。此外,还考虑了促进废物回收的政策工具,还讨论了它们对危险废物管理成本和风险的影响。该模型在Lingo优化求解器中进行编码和计算,并且采用增强ε-concrareaint方法来生成多目标优化问题的帕累托最优曲线。在数值实验中说明了不同目标之间的权衡。

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