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Chance‐constrained multi‐objective approach for hazardous materials routing and scheduling under demand and service time uncertainty
Author(s) -
Moghaddam Kamran S.,
Azadian Farshid
Publication year - 2020
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.1718
Subject(s) - vehicle routing problem , computer science , hazardous waste , scheduling (production processes) , mathematical optimization , pareto principle , job shop scheduling , routing (electronic design automation) , operations research , engineering , mathematics , computer network , waste management
The transportation of hazardous materials (hazmat) is a challenging problem that often requires a trade‐off between conflicting objectives. In practice, the complexity of the problem is exacerbated due to the lack of sufficient and reliable historical data. In this research, a stochastic multi‐objective optimization model for hazardous materials (hazmat) vehicle routing and scheduling problem is developed. The goal is to find optimal links and routes to obtain a trade‐off between the safe and fast distribution of hazmat through a transport network under customers' demand and service time uncertainty. We utilized a hybrid game theory based compromise programming to develop a solution algorithm to determine the Pareto‐optimal solutions, which are based on the total travel distance and total risk imposed on the transportation process. Computational results of a realistic numerical case study demonstrate the effectiveness of the proposed model and the solution algorithm in obtaining Pareto‐optimal solutions.