Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches

Ali Heidari (), Din Mohammad Imani (), Mohammad Khalilzadeh () and Mahdieh Sarbazvatan ()
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Ali Heidari: Iran University of Science and Technology
Din Mohammad Imani: Iran University of Science and Technology
Mohammad Khalilzadeh: CENTRUM Católica Graduate Business School
Mahdieh Sarbazvatan: Iran University of Science and Technology

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 9, No 10, 9163-9199

Abstract: Abstract Nowadays organizations outsource transportation of goods or services to reduce cost which leads to a particular type of problem called open location-routing. Also, each logistic organization possesses a limited number of specific vehicles that may not be enough in certain circumstances. This issue indicates the importance of simultaneously considering both open and closed routs. On the other hand, the growing concerns about the detrimental environmental impacts of human activities reveal the necessity of paying attention to environmental issues in logistics. In this study, a bi-objective mathematical programming model is proposed for two-echelon close and open location-routing problem (2E-COLRP) including two echelons of factories, depots and customers to minimize costs and CO2 emissions. The proposed model finds the optimal routs, optimal number of vehicles and facilities as well as the locations of facilities. The augmented epsilon constraint method is used as an exact method to solve the small-sized problems. Due to complexity of model, two metaheuristic algorithms named MOGWO and NSGA-II are utilized to tackle the problems. The efficiency of two aforementioned algorithms is evaluated in terms of several indices considering 22 problem instances with various sizes. The results show that MOGWO performs better than NSGA-II.

Keywords: Open location routing; Closed location routing; Environmental impact; Metaheuristic; MOGWO; NSGA-II (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02429-w

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