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

Abstract

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.

KEYWORDS:

• Hazardous waste
• location-routing problem
• risks
• robust possibilistic programming

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Fatemeh Delfani

Fatemeh Delfani is a PhD student in the Department of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran. Her interests span from Supply Chain Management, Mathematical Modeling and Meta-heuristic Algorithms.

Abolfazl Kazemi

Abolfazl Kazemi is an Associate Professor in the Department of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran. His research interests include Logistic and Supply Chain Management, Intelligent Information Systems, Multi-agent Systems, Fuzzy Set Theory.

Seyed Mohammad SeyedHosseini

Seyed Mohammad SeyedHosseini is a Professor of Industrial Engineering at Iran University of Science and Technology. His research interests are in the areas of Preventive Maintenance Planning, Transportation Systems Modeling, Logistic and Supply Chain Management, Meta-heuristic Algorithms.

Seyed Taghi Akhavan Niaki

Seyed Taghi Akhavan Niaki is a distinguished Professor of Industrial Engineering at Sharif University of Technology. His research interests are in the areas of Quality Engineering, Applied Statistics, Simulation Modeling and Analysis, and Operations Research. He received his BSc in Industrial Engineering from Sharif University of Technology in 1979, his Master's and his PhD degrees both in Industrial Engineering from West Virginia University in 1989 and 1992, respectively. He is the Editor-In-Chief of Scientia Iranica, the Editor of Scientia Iranica - Transactions E, the Editor-In-Chief of Sharif Journal of Industrial Engineering and Management (in Persian), the Board Member of several international journals, and a member of Alpha-Pi-Mu.