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.

Automated summary

The study introduces a multi-objective mathematical model to address hazardous waste management issues by simultaneously considering transportation and population risks as well as total costs. Additionally, a basic possibilistic chance-constrained programming method and a robust possibilistic programming model were developed to deal with parameter uncertainty. The robust possibilistic programming model outperformed the basic possibilistic chance-constrained programming model in obtaining better solutions for different scenarios and sensitivities.