A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions

Abstract

Industrialization and population growth have been accompanied by many problems such as waste management worldwide. Waste management and reduction have a vital role in national management. The presents study represents a multi-objective location-routing problem for hazardous wastes. The model was solved using Non dominated Sorting Genetic Algorithm-II, Multi-Objective Particle Swarm Optimization, Multi-Objective Invasive Weed Optimization, Pareto Envelope-based Selection Algorithm, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer algorithms. The findings revealed that the Multi-Objective Invasive Weed Optimization algorithm was the best and the most efficient among the algorithms used in this study. Obtaining income from the incineration of the wastes and reducing the risk of COVID-19 infection are the first innovation of the present study, which considered in the presented model. The second innovation is that uncertainty was considered for some of the crucial parameters of the model while the robust fuzzy optimization model was applied. Besides, the model was solved using several meta-heuristic algorithms such as Multi-Objective Invasive Weed Optimization, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer, which were rarely used in literature. Eventually, the most efficient algorithm was identified by comparing the considered algorithms.

Robust Bi-Level Optimization for Maritime Emergency Materials Distribution in Uncertain Decision-Making Environments

“…A nonlinear integer open locationrouting model was constructed by Wang et al [27] that considered travel time, total cost, and reliability when distributing post-disaster relief materials, and they proposed a nondominated sorting differential evolution algorithm and a non-dominated sorting genetic algorithm to solve it. Raeisi et al [28] constructed a robust fuzzy multi-objective optimization model to solve the hazardous waste management problem, which was solved using various heuristic algorithms and analyzed comparatively. Shen et al [29] proposed a triangular fuzzy function to obtain the fuzzy demand considering the uncertainty of the demand in the disaster area, constructed a multi-objective model considering the carbon emissions, and used a two-stage hybrid algorithm to solve the problem.…”

El problema de localización y ruteo con múltiples objetivos: una revisión de literatura

“…Sin embargo, son (43) quienes introducen el concepto de problema de localización y ruteo verde o GLRP para los residuos peligrosos, en el cual proponen un estudio que minimiza simultáneamente costos, riesgo de transporte y localización y emisiones de CO 2 dentro de sus objetivos. Este enfoque hacia la minimización de emisiones ha sido evaluado en estudios posteriores: (44)(45)(46)(47).…”

Z-trapezoidal risk assessment for multi-objective Hazmat routing model with time windows

“…A robust fuzzy method controlled uncertain parameters, such as demand, transmission, and distribution costs. Raeisi and Jafarzadeh Ghoushchi [41] presented a multi-objective location-routing problem for hazardous wastes. The amount of generated waste and transportation costs were formulated as uncertain data in the form of trapezoidal fuzzy numbers.…”