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

H Yu, WD Solvang - International journal of environmental research and …, 2016 - mdpi.com
International journal of environmental research and public health, 2016mdpi.com
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 …
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.
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