A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm
In Inventory Routing Problem (IRP), which is one of the most important logistics problems, decisions regarding the distribution and inventory management must be made by an integrated managerial approach. In this type of problems, decision maker usually has the option to use several types of vehicles...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
University of Qom
2022-09-01
|
| Series: | مدیریت مهندسی و رایانش نرم |
| Subjects: | |
| Online Access: | https://jemsc.qom.ac.ir/article_878_250af5b71bdd3e71fefa2b69f7a88804.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832577574542245888 |
|---|---|
| author | Mohsen Zamani Mahdi Alinaghian |
| author_facet | Mohsen Zamani Mahdi Alinaghian |
| author_sort | Mohsen Zamani |
| collection | DOAJ |
| description | In Inventory Routing Problem (IRP), which is one of the most important logistics problems, decisions regarding the distribution and inventory management must be made by an integrated managerial approach. In this type of problems, decision maker usually has the option to use several types of vehicles to form a fleet with appropriate size and composition in order to minimize both inventory and transportation costs. Considering the amount of pollution produced, in this problem, may reduce pollution . This paper proposes a new model for green inventory routing problem with heterogeneous fleet. The objectives of the proposed model are to minimize the emissions, the fleet, routing and inventory costs. Due to the NP-hard nature of the assessed problem, a meta-heuristic algorithm based on Quantum Evolutionary Algorithm (QEA) is proposed. To evaluate the performance of the proposed algorithm, its results are compared with the results of exact method and basic Algorithm. The results of these comparisons indicate the good performance of the proposed algorithm. |
| format | Article |
| id | doaj-art-0a823df049bb4c0aa8825de16b53ee40 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2022-09-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-0a823df049bb4c0aa8825de16b53ee402025-01-30T20:18:08ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752022-09-0172668810.22091/jemsc.2017.878878A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary AlgorithmMohsen Zamani0Mahdi Alinaghian1MSc., Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran.Assistant Prof., Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran.In Inventory Routing Problem (IRP), which is one of the most important logistics problems, decisions regarding the distribution and inventory management must be made by an integrated managerial approach. In this type of problems, decision maker usually has the option to use several types of vehicles to form a fleet with appropriate size and composition in order to minimize both inventory and transportation costs. Considering the amount of pollution produced, in this problem, may reduce pollution . This paper proposes a new model for green inventory routing problem with heterogeneous fleet. The objectives of the proposed model are to minimize the emissions, the fleet, routing and inventory costs. Due to the NP-hard nature of the assessed problem, a meta-heuristic algorithm based on Quantum Evolutionary Algorithm (QEA) is proposed. To evaluate the performance of the proposed algorithm, its results are compared with the results of exact method and basic Algorithm. The results of these comparisons indicate the good performance of the proposed algorithm.https://jemsc.qom.ac.ir/article_878_250af5b71bdd3e71fefa2b69f7a88804.pdfcomprehensive modal emission model (cmem)fuel consumptioninventory routing problem with heterogeneous fleetquantum evolutionary algorithm |
| spellingShingle | Mohsen Zamani Mahdi Alinaghian A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm مدیریت مهندسی و رایانش نرم comprehensive modal emission model (cmem) fuel consumption inventory routing problem with heterogeneous fleet quantum evolutionary algorithm |
| title | A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm |
| title_full | A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm |
| title_fullStr | A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm |
| title_full_unstemmed | A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm |
| title_short | A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm |
| title_sort | new model of fleet size and mix green inventory routing problem solution multi objective quantum evolutionary algorithm |
| topic | comprehensive modal emission model (cmem) fuel consumption inventory routing problem with heterogeneous fleet quantum evolutionary algorithm |
| url | https://jemsc.qom.ac.ir/article_878_250af5b71bdd3e71fefa2b69f7a88804.pdf |
| work_keys_str_mv | AT mohsenzamani anewmodeloffleetsizeandmixgreeninventoryroutingproblemsolutionmultiobjectivequantumevolutionaryalgorithm AT mahdialinaghian anewmodeloffleetsizeandmixgreeninventoryroutingproblemsolutionmultiobjectivequantumevolutionaryalgorithm AT mohsenzamani newmodeloffleetsizeandmixgreeninventoryroutingproblemsolutionmultiobjectivequantumevolutionaryalgorithm AT mahdialinaghian newmodeloffleetsizeandmixgreeninventoryroutingproblemsolutionmultiobjectivequantumevolutionaryalgorithm |