Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm
One of the most important issues of concern to human societies in recent years is urban waste management that is one of the main requirements of each city, and without any notice of it, it can be problematic for it and even residents of the surrounding villages. Urban areas generate the highest amou...
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| Format: | Article |
| Language: | fas |
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Semnan University
2019-06-01
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| Series: | مجله مدل سازی در مهندسی |
| Subjects: | |
| Online Access: | https://modelling.semnan.ac.ir/article_3912_c58c5b906f83788323230503d2009de4.pdf |
| _version_ | 1827342325092712448 |
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| author | Erfan Babaee Tirkolaee Iraj Mahdavi Mir Mehdi Seyyed Esfahani |
| author_facet | Erfan Babaee Tirkolaee Iraj Mahdavi Mir Mehdi Seyyed Esfahani |
| author_sort | Erfan Babaee Tirkolaee |
| collection | DOAJ |
| description | One of the most important issues of concern to human societies in recent years is urban waste management that is one of the main requirements of each city, and without any notice of it, it can be problematic for it and even residents of the surrounding villages. Urban areas generate the highest amount of waste and consequently, they need an efficient system for collecting and disposing of waste where its determination and stabilization is very difficult and costly. In this regard, this paper examines the multi-trip vehicle routing problem with time windows specific to the urban waste collection, with the goal is to minimize the total cost including routing costs, the earliness and lateness penalty cost for violating the service time windows and the usage costs of vehicles. To solve the problem in practical dimensions, grey wolf optimization (GWO) algorithm is developed where its performance is tested compared to CPLEX solver of GAMS and simulated annealing (SA) algorithm. The obtained results demonstrate that the proposed GWO have an acceptable performance to generate high-quality solutions. Finally, to study the behavior of the objective function versus the real-world demand parameter changes, a sensitivity analysis is performed on this parameter and the optimal management policy is analyzed.ed. |
| first_indexed | 2024-03-07T22:06:06Z |
| format | Article |
| id | doaj.art-53044cca4fc9458a95f953682f35139e |
| institution | Directory Open Access Journal |
| issn | 2008-4854 2783-2538 |
| language | fas |
| last_indexed | 2024-03-07T22:06:06Z |
| publishDate | 2019-06-01 |
| publisher | Semnan University |
| record_format | Article |
| series | مجله مدل سازی در مهندسی |
| spelling | doaj.art-53044cca4fc9458a95f953682f35139e2024-02-23T19:06:13ZfasSemnan Universityمجله مدل سازی در مهندسی2008-48542783-25382019-06-0117579311010.22075/jme.2019.16445.16333912Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithmErfan Babaee Tirkolaee0Iraj Mahdavi1Mir Mehdi Seyyed Esfahani2Department of Industrial Engineering, Mazandaran University of Science & Technology, Babol, IranDepartment of Industrial Engineering, Mazandaran University of Science and TechnologyDepartment of Industrial Engineering, Amirkabir University of TechnologyOne of the most important issues of concern to human societies in recent years is urban waste management that is one of the main requirements of each city, and without any notice of it, it can be problematic for it and even residents of the surrounding villages. Urban areas generate the highest amount of waste and consequently, they need an efficient system for collecting and disposing of waste where its determination and stabilization is very difficult and costly. In this regard, this paper examines the multi-trip vehicle routing problem with time windows specific to the urban waste collection, with the goal is to minimize the total cost including routing costs, the earliness and lateness penalty cost for violating the service time windows and the usage costs of vehicles. To solve the problem in practical dimensions, grey wolf optimization (GWO) algorithm is developed where its performance is tested compared to CPLEX solver of GAMS and simulated annealing (SA) algorithm. The obtained results demonstrate that the proposed GWO have an acceptable performance to generate high-quality solutions. Finally, to study the behavior of the objective function versus the real-world demand parameter changes, a sensitivity analysis is performed on this parameter and the optimal management policy is analyzed.ed.https://modelling.semnan.ac.ir/article_3912_c58c5b906f83788323230503d2009de4.pdfmulti-trip vehicle routing problemurban waste collectiongrey wolf optimization algorithmsimulated annealing algorithm |
| spellingShingle | Erfan Babaee Tirkolaee Iraj Mahdavi Mir Mehdi Seyyed Esfahani Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm مجله مدل سازی در مهندسی multi-trip vehicle routing problem urban waste collection grey wolf optimization algorithm simulated annealing algorithm |
| title | Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| title_full | Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| title_fullStr | Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| title_full_unstemmed | Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| title_short | Solving the multi-trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| title_sort | solving the multi trip vehicle routing problem with time windows in urban waste management using grey wolf optimization algorithm |
| topic | multi-trip vehicle routing problem urban waste collection grey wolf optimization algorithm simulated annealing algorithm |
| url | https://modelling.semnan.ac.ir/article_3912_c58c5b906f83788323230503d2009de4.pdf |
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