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

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 maker...

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Veröffentlicht in:International journal of environmental research and public health Jg. 13; H. 6; S. 548
Hauptverfasser: Yu, Hao, Solvang, Wei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 31.05.2016
MDPI
Schlagworte:
Decision Making
Environment
Hazardous materials
Hazardous Waste
Humans
Integer programming
Mathematical models
Models, Statistical
Municipal solid waste
Objectives
Quality Improvement
Refuse Disposal
Software
Transportation - standards
Waste Management
Waste management industry
Norway
augmented ε-constraint method
multi-objective programming
location-routing problem
mixed integer programming
hazardous waste management
ISSN:1660-4601, 1661-7827, 1660-4601
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Zusammenfassung: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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ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph13060548