An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution
The growing trend of natural resources consumption has caused irreparable losses to the environment. The scientists believe that if environmental degradation continues at its current pace, the prospect of human life will be shrouded in mystery. One of the most effective ways to deal with the environ...
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| Format: | Article |
| Language: | English |
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University of Zagreb, Faculty of Transport and Traffic Sciences
2017-09-01
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| Series: | Promet (Zagreb) |
| Subjects: | |
| Online Access: | https://traffic.fpz.hr/index.php/PROMTT/article/view/2193 |
| _version_ | 1811335119815835648 |
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| author | Sara Nakhjirkan Farimah Mokhatab Rafiei |
| author_facet | Sara Nakhjirkan Farimah Mokhatab Rafiei |
| author_sort | Sara Nakhjirkan |
| collection | DOAJ |
| description | The growing trend of natural resources consumption has caused irreparable losses to the environment. The scientists believe that if environmental degradation continues at its current pace, the prospect of human life will be shrouded in mystery. One of the most effective ways to deal with the environmental adverse effects is by implementing green supply chains. In this study a multilevel mathematical model including supply, production, distribution and customer levels has been presented for routing–location–inventory
in green supply chain. Vehicle routing between distribution centres and customers has been considered in the model. Establishment place of distribution centres among potential places is determined by the model. The distributors use continuous review policy (r, Q) to control the inventory. The proposed model object is to find an optimal supply chain with minimum costs. To validate the proposed model and measure its compliance with real world problems, GAMS IDE/Cplex has been used. In order to measure the efficiency of the proposed model in large scale problems, a genetic algorithm has been used. The results confirm the efficiency of the proposed model as a practical tool for decision makers to solve location-inventory-routing problems in green supply chain. The proposed GA could reduce the solving time by 85% while reaching on the average 97% of optimal solution compared with exact method. |
| first_indexed | 2024-04-13T17:19:24Z |
| format | Article |
| id | doaj.art-5818539fce224f0cbe7a69f15726a90b |
| institution | Directory Open Access Journal |
| issn | 0353-5320 1848-4069 |
| language | English |
| last_indexed | 2024-04-13T17:19:24Z |
| publishDate | 2017-09-01 |
| publisher | University of Zagreb, Faculty of Transport and Traffic Sciences |
| record_format | Article |
| series | Promet (Zagreb) |
| spelling | doaj.art-5818539fce224f0cbe7a69f15726a90b2022-12-22T02:38:02ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692017-09-0129439140010.7307/ptt.v29i4.21932193An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based SolutionSara Nakhjirkan0Farimah Mokhatab Rafiei1PhD student at Isfahan University of Technology, Industrial and systems engineering faculty, Isfahan University of TechnologyAssociated Professor Industrial and systems engineering faculty, Tarbiat Modares UniversityThe growing trend of natural resources consumption has caused irreparable losses to the environment. The scientists believe that if environmental degradation continues at its current pace, the prospect of human life will be shrouded in mystery. One of the most effective ways to deal with the environmental adverse effects is by implementing green supply chains. In this study a multilevel mathematical model including supply, production, distribution and customer levels has been presented for routing–location–inventory in green supply chain. Vehicle routing between distribution centres and customers has been considered in the model. Establishment place of distribution centres among potential places is determined by the model. The distributors use continuous review policy (r, Q) to control the inventory. The proposed model object is to find an optimal supply chain with minimum costs. To validate the proposed model and measure its compliance with real world problems, GAMS IDE/Cplex has been used. In order to measure the efficiency of the proposed model in large scale problems, a genetic algorithm has been used. The results confirm the efficiency of the proposed model as a practical tool for decision makers to solve location-inventory-routing problems in green supply chain. The proposed GA could reduce the solving time by 85% while reaching on the average 97% of optimal solution compared with exact method.https://traffic.fpz.hr/index.php/PROMTT/article/view/2193supply chain networkstochastic mathematical programminglocation-inventory-routing problemGenetic Algorithm |
| spellingShingle | Sara Nakhjirkan Farimah Mokhatab Rafiei An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution Promet (Zagreb) supply chain network stochastic mathematical programming location-inventory-routing problem Genetic Algorithm |
| title | An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution |
| title_full | An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution |
| title_fullStr | An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution |
| title_full_unstemmed | An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution |
| title_short | An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution |
| title_sort | integrated multi echelon supply chain network design considering stochastic demand a genetic algorithm based solution |
| topic | supply chain network stochastic mathematical programming location-inventory-routing problem Genetic Algorithm |
| url | https://traffic.fpz.hr/index.php/PROMTT/article/view/2193 |
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