A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem

Abstract

Hazardous material transportation is an integral part of industries that pose significant risks. Hazardous material transportation risk of is proportional to the volume of materials transferred, the length of the link, and the population density, which varies over time. By modeling the effects of time on population density, this paper presents a multi-objective time-dependent hazardous materials routing problem for efficiently managing hazardous material transportation. The proposed model's objectives include the reduction of transportation risks and travel costs. Given the uncertainty associated with hazardous materials routing, an interval type-2 fuzzy logic controller is used to estimate risk; its inputs include population density, vehicle load, link length, and time of day. A type-2 fuzzy multi-objective evolutionary algorithm based on decomposition is used to optimize the proposed model and an adaptive large neighborhood search to enhance the local neighbor search mechanism. Additionally, by utilizing the nadir reference point, the distribution of Pareto front approximation is improved. Furthermore, a new metric is introduced to evaluate the dispersion of Pareto front approximation. The proposed method is compared to three other state-of-the-art evolutionary algorithms using eleven different performance metrics for validation. Then, using the multiple-criteria decision-making approach, the meta-heuristics algorithms are evaluated. The obtained results demonstrate the proposed solution method algorithm's competitiveness and superiority over the other three evolutionary algorithms.