Developing a hazardous waste management system with consideration of health, safety, and environment. (March 2020)

• Record Type: Journal Article
• Authors: Farrokhi-Asl, Hamed; Makui, Ahmad; Ghousi, Rouzbeh; Rabbani, Masoud
• Is Part Of: Computers & electrical engineering. Volume 82(2020)
• Publication Date: 2020-03
• Subjects: Waste collection problem -- HSE -- Multi objective optimization -- Ɛ-constraint method -- Metaheuristic algorithms; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106553
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: We presents a new mathematical model for hazardous waste collection problem. The paper considers a HSE issues for the first time in the literature of this field. Two algorithms including NSGA-II and epsilon constraint method are applied to solve the problem. A simple solution representation is provided to encode the problem. A new network is considered for waste collection problem. Abstract: This paper presents a novel mathematical model for hazardous waste collection problem. The study aims to introduce a model in order to improve health, safety, environment (HSE) issues for hazardous waste collection problem in addition to considering operational cost. In addition, technologies which will be applied at each facility are investigated. To extend previous networks in this field of study, the vehicles' depot are considered, . In order to tackle the problem, ɛ-constraint and non-dominated sorting genetic algorithm II (NSGA-II) methods are applied. According to the results, we can state that NSGA-II mean value of comparison metrics are equivalent to the results of ɛ-constraint with confidence level of 95%. Moreover, the sum of the distance's mean from the ideal point for ɛ-constraint method is 4% less than NSGA-II which can be concluded as an acceptable result for NSGA-II algorithm. All in all, The presented model can help managers and decision makers to have a more comprehensive and thorough understanding the HSE issues with respect to the operational cost in the field of waste collection network design.