Using modified metaheuristic algorithms to solve a hazardous waste collection problem considering workload balancing and
- PDF / 3,911,291 Bytes
- 28 Pages / 595.276 x 790.866 pts Page_size
- 42 Downloads / 164 Views
(0123456789().,-volV)(0123456789(). ,- volV)
METHODOLOGIES AND APPLICATION
Using modified metaheuristic algorithms to solve a hazardous waste collection problem considering workload balancing and service time windows Masoud Rabbani1 • Alireza Nikoubin1 • Hamed Farrokhi-Asl2
Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract 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. Keywords Hazardous waste Location routing problem Workload balancing Multi-objective optimization Metaheuristic algorithms
1 Introduction Owing to the progress and extension of technologies, science, and industries, the hazardous wastes’ volume produced by human activities have increased rapidly, and consequently associated risks included in treatment, recycling, disposing, and transportation of these dangerous wastes and especially environmental issues, have become Communicated by V. Loia. & Masoud Rabbani [email protected] 1
School of Industrial Engineering, College of Engineering, University of Tehran, P.O.Box: 11155-4563, Tehran, Iran
2
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
the more attractive subject for the researchers. Hazardous waste can be characterized as flammable, irritant, poisonous, carcinogenic, toxic, infectious, and reactive (Nema and Gupta 1999). There are various ranges of industr
Data Loading...
