Hazardous Waste Location-routing Problem Research Articles

A Green Hazardous Waste Location-routing Problem Considering the Risks Associated with Transportation and Population

The researches on environmental and sustainability are an active topic, especially in the waste management. As such, the hazardous waste optimization is an active research topic in developing countries which may be integrated with carbon emissions and green subjects. This grand challenge motivates the current research to contribute a new multi-objective optimization model to address the green hazardous waste location-routing problem. The proposed multi-objective optimization model establishes four objectives simultaneously for the first time. In addition to the total cost and the greenhouse gas emissions of the transportation systems as the two main objectives, another objective function aims to minimize the risk of transportation of the hazardous waste alongside the waste residue associated with the people’s exposure around transportation paths. Furthermore, the total risk linked with the population in a certain radius around the treatment and disposal centers is minimized. As the proposed model is complex with conflicting objectives, several multi-objective decision making (MODM) tools are employed and compared with each other based on different test problems associated with an industrial example. Based on the solution quality and the computational time, the technique for the order of preference by similarity to the ideal solution (TOPSIS) is selected as the strongest technique to assess the performances of all five MODM methodologies.

Using modified metaheuristic algorithms to solve a hazardous waste collection problem considering workload balancing and service time windows

Hazardous wastes’ volume produced by human activities has increased in recent years. Consequently, associated risks involved in the treatment, recycling, disposing, and transportation of these hazardous materials have become more attractive for the researchers. In this study, we propose a new model for hazardous waste location routing problem. Appending the service time window and workload balance to the previous mathematical models can be taken into account as the major contributions of this study. Three objective functions including two systematic goals (cost and risk) and one social goal (workload balancing) have been considered for the model. Compatibility between wastes and a heterogeneous fleet of vehicles, which are rarely investigated in the literature, is discussed in this paper. Since the proposed model is classified as a multi-objective model, three multi-objective evolutionary algorithms, namely Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm II (PESA-II), and Strength Pareto Evolutionary Algorithm II (SPEA-II) are employed. As two other innovations, an adaptive penalty function is developed and the PESA-II is modified by removing replicated solutions from its archive and their obtained results are discussed. Finally, by experimenting a number of test problems in different sizes, it is demonstrated that proposed modified PESA-II and SPEA-II perform better than NSGA-II in most of comparison metrics including feasible answers exploration, CPU time, spacing metric, inverted generational distance, quality metric, etc., whereas, NSGA-II creates more spread Pareto frontiers which are suitable for decision-maker to choose, from among a range of different options.

A novel robust possibilistic programming approach for the hazardous waste location-routing problem considering the risks of transportation and population

Nowadays, fast growth in industrial transformation and urbanization pushes the management of hazardous waste into a crisis for all markets. In this study, a multi-objective mathematical model is introduced to address a new version of the hazardous waste location-routing problem. As another multi-objective optimization model in this research area, the objective functions are minimizing the total costs, the overall risk associated with sending the hazardous waste, and the site risk related to the population in a given distance around the facilities. With regards to the literature and as far as the authors know, this is the first attempt to consider both risks of transportation and population simultaneously in addition to the total cost. Another contribution of this research is the development of a basic possibilistic chance-constrained programming (BPCCP) approach. After that, a robust possibilistic programming (RPP) model of the proposed problem is introduced to deal with the uncertainty of the model’s parameters. While the applicability of the proposed models is addressed, it is revealed that the RPP model obtains better solutions in comparison with the BPCCP model for different realizations and sensitivities. Finally, practical insights are concluded from the results.

A profit-oriented mathematical model for hazardous waste locating- routing problem

Hazardous waste management (HWM) deals with the safe, efficient and cost effective collection, transportation, treatment and disposal of wastes. This paper presents a profit- oriented mixed integer mathematical model for the hazardous waste location-routing problem, which incorporates the energy recovery from waste and the application of the polluter pays principle. The suggested model decides on the locations and numbers of recycling, incineration, sterilization, interim storage and disposal centers and on how to transfer various types of hazardous waste and waste residues among these centers from the perspective of environmental protection. The proposed model was implemented in a real life case study and tested on various hypothetical problem instances. In addition, an extended formulation was developed on a rolling horizon basis through the objective function of Net Present Value (NPV) to analyze the overall profitability of the entire HWM system for long-term planning and a sensitivity study was conducted on different interest rates. The results show that the model is applicable to real-life waste management systems and it can provide effective solutions for large-scale HWM problems.

A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation

The present study extends a multi-objective mathematical model in the context of industrial hazardous waste management, which covers the integrated decisions of three levels with locating, vehicle routing, and inventory control. Analyzing these decisions simultaneously not only may lead to the most effective structure in the waste management network, but also may reduce the potential risk of managing the hazardous waste. Furthermore, because of the inherent complexity of the waste management system, uncertainty is inevitable and should be acknowledged to guarantee reliability in the decision-making process. From this perspective, the proposed model is novel in the following three aspects: (1) shifting from a deterministic to stochastic environment; (2) considering a multi-period planning horizon; and (3) incorporating the inventory decisions into the problem. The problem is formulated as a multi-objective stochastic Mixed-Integer Nonlinear Programming (MINLP) model, which can be easily converted into a MILP one. In terms of methodological contribution, a new simheuristic approach that is an integration of Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and Monte Carlo simulation is developed to overcome the stochastic combinatorial optimization problem of this study. Our findings verify the efficiency of the proposed approach as it is able to find a high-quality solution within a relatively reasonable computational time.

Using metaheuristic algorithms to solve a multi-objective industrial hazardous waste location-routing problem considering incompatible waste types

Rapid progress in technology is a primary cause of acceleration in the rate of the industrial hazardous waste generation all over the world. Management of hazardous waste has magnetized researcher's attention because of its considerable impacts on the economy, ecology, and the environment. In this regard, this paper addresses a new industrial hazardous waste location-routing problem by putting emphasis on some new aspects in its formulation such as considering restriction about the incompatibility between some kinds of wastes and incorporating routing decisions into the model. Simultaneously minimization of three significant criteria, including total cost, total transportation risk of hazardous waste related to population exposure, and site risk persuades authors to implement two multi-objective evolutionary algorithms, Nondominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) for tackling the problem. The results obtained from experiments on several problem instances confirm the superiority of NSGA-II over MOPSO in terms of most of the evaluation metrics. Therefore, the significance of the paper is firstly the novelty of the model, and secondly, the comparison of two solution methods allows for the identification of the method resulting in the best results.

A multi-objective mathematical model for the industrial hazardous waste location-routing problem

Industrial hazardous waste management involves the collection, transportation, treatment, recycling and disposal of industrial hazardous materials that pose risk to their surroundings. In this paper, a new multi-objective location-routing model is developed, and implemented in the Marmara region of Turkey. The aim of the model is to help decision makers decide on locations of treatment centers utilizing different technologies, routing different types of industrial hazardous wastes to compatible treatment centers, locations of recycling centers and routing hazardous waste and waste residues to those centers, and locations of disposal centers and routing waste residues there. In the mathematical model, three criteria are considered: minimizing total cost, which includes total transportation cost of hazardous materials and waste residues and fixed cost of establishing treatment, disposal and recycling centers; minimizing total transportation risk related to the population exposure along transportation routes of hazardous materials and waste residues; and minimizing total risk for the population around treatment and disposal centers, also called site risk. A lexicographic weighted Tchebycheff formulation is developed and computed with CPLEX software to find representative efficient solutions to the problem. Data related to the Marmara region is obtained by utilizing Arcview 9.3 GIS software and Marmara region geographical database.

A new model for the hazardous waste location-routing problem

Hazardous waste management involves the collection, transportation, treatment and disposal of hazardous wastes. In this paper a new multiobjective location-routing model is proposed. Our model also includes some constraints, which were observed in the literature but were not incorporated into previous models. The aim of the proposed model is to answer the following questions: where to open treatment centers and with which technologies, where to open disposal centers, how to route different types of hazardous waste to which of the compatible treatment technologies, and how to route waste residues to disposal centers. The model has the objective of minimizing the total cost and the transportation risk. A large-scale implementation of the model in the Central Anatolian region of Turkey is presented.