Abstract

The management of hazardous wastes in regions is required to design a multi-echelon network with multiple facilities including recycling, treatment and disposal centers servicing the transportation, recycling, treatment and disposal procedures of hazardous wastes and waste residues. The multi-period network design problem within is to determine the location of waste facilities and allocation/transportation of wastes/residues in each period during the planning horizon, such that the total cost and total risk in the location and transportation procedures are minimized. With consideration of the life cycle capacity of disposal centers, we formulate the problem as a bi-objective mixed integer linear programming model in which a unified modeling strategy is designed to describe the closing of existing waste facilities and the opening of new waste facilities. By exploiting the characteristics of the proposed model, an augmented -constraint algorithm is developed to solve the model and find highly qualified representative non-dominated solutions. Finally, computational results of a realistic case demonstrate that our algorithm can identify obviously distinct and uniformly distributed representative non-dominated solutions within reasonable time, revealing the trade-off between the total cost and total risk objectives efficiently. Meanwhile, the multi-period network design optimization is superior to the single-period optimization in terms of the objective quality.

Highlights

  • During the past years, along with the rapid development of economy and the improvement of people’s living standard, large quantities of hazardous wastes belonging to different categories are produced in the processes of industrial production and manufacturing, medical services and social life

  • This paper focuses on the multi-period network design problem in the long-term design of an integrated regional hazardous waste management system with multiple types of hazardous wastes, waste facilities and treatment technologies

  • Given the production of hazardous wastes, candidate waste facilities and related cost, risk and capacity parameters in each period of the planning horizon, the multi-period network design problem in a regional hazardous waste management system is to determine the location of recycling centers, treatment centers and disposal centers and the allocation/transportation of six hazardous wastes/waste residues from generation nodes to waste facilities and between these waste facilities, such that the wastes and residues produced in each period are treated properly and the opening and closing of each waste facility is consistent among periods, while the total cost and total risk incurred in the location and transportation procedures of the whole planning horizon is minimized

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Summary

Introduction

Along with the rapid development of economy and the improvement of people’s living standard, large quantities of hazardous wastes belonging to different categories are produced in the processes of industrial production and manufacturing, medical services and social life. List and Mirchandani [12] firstly introduced the single period regional hazardous waste network design problem with multiple types of hazardous wastes and treatment technologies They proposed a multi-objective path-based network design model and solved it with a weighted-sum algorithm. Najm et al [33] established a single objective multi-period network design model for a regional solid waste management system with treatment and disposal centers. In light of the shortages of related works, in this paper we aim at presenting a theoretically rigorous multi-objective model and a practically feasible multi-objective algorithm for the multi-period network design problem in regional hazardous waste management systems with multiple types of hazardous wastes, waste facilities and treatment technologies. We formulate the multi-period hazardous waste network design problem as a bi-objective mixed integer linear programming model to minimize the total cost and total risk in the location and transportation procedures simultaneously.

Problem Description
Notations
Model Formulation
Augmented ε-Constraint Algorithm
Case Study
Case Description and Parameter Setting
Computational Results
The Value of Multi-Period Optimization
Sensitivity Analysis
Conclusions
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