Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand
The effective distribution of relief to an emergency logistics system plays a crucial role during the disaster response phase. Considering stochastic characteristics of relief demand, this study investigates the robust optimization of a multi-objective multi-period location-routing problem for epide...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9605259/ |
| _version_ | 1811209829197283328 |
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| author | Shengjie Long Dezhi Zhang Yijing Liang Shuangyan Li Wanru Chen |
| author_facet | Shengjie Long Dezhi Zhang Yijing Liang Shuangyan Li Wanru Chen |
| author_sort | Shengjie Long |
| collection | DOAJ |
| description | The effective distribution of relief to an emergency logistics system plays a crucial role during the disaster response phase. Considering stochastic characteristics of relief demand, this study investigates the robust optimization of a multi-objective multi-period location-routing problem for epidemic logistics, a special emergency logistics, with uncertain scenarios. A corresponding robust multi-objective multi-period optimization model is proposed, which aims to determine the optimal location of temporary relief distribution centres and route planning simultaneously. The optimization objectives include the total travel time, the total cost, and the disutility of relief service. To solve the above optimization model, a preference-inspired co-evolutionary algorithm with Tchebycheff decomposition (PICEA-g-td) is given. The performance of the proposed PICEA-g-td is evaluated by comparing it with NSGA-II, MOEA/D and PICEA-g. The experimental results show that the proposed algorithm performs better than the other three algorithms in terms of the solution quality. Finally, some useful management insights are obtained. |
| first_indexed | 2024-04-12T04:45:35Z |
| format | Article |
| id | doaj.art-349f04c864e14807b79ca7286b9ea197 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T04:45:35Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-349f04c864e14807b79ca7286b9ea1972022-12-22T03:47:30ZengIEEEIEEE Access2169-35362021-01-01915191215193010.1109/ACCESS.2021.31257469605259Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain DemandShengjie Long0https://orcid.org/0000-0002-1869-320XDezhi Zhang1https://orcid.org/0000-0003-1172-0161Yijing Liang2https://orcid.org/0000-0001-9710-0478Shuangyan Li3Wanru Chen4School of Traffic and Transportation Engineering, Central South University, Changsha, ChinaSchool of Traffic and Transportation Engineering, Central South University, Changsha, ChinaSchool of Management and Engineering, Nanjing University, Nanjing, ChinaCollege of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, ChinaSchool of Traffic and Transportation Engineering, Central South University, Changsha, ChinaThe effective distribution of relief to an emergency logistics system plays a crucial role during the disaster response phase. Considering stochastic characteristics of relief demand, this study investigates the robust optimization of a multi-objective multi-period location-routing problem for epidemic logistics, a special emergency logistics, with uncertain scenarios. A corresponding robust multi-objective multi-period optimization model is proposed, which aims to determine the optimal location of temporary relief distribution centres and route planning simultaneously. The optimization objectives include the total travel time, the total cost, and the disutility of relief service. To solve the above optimization model, a preference-inspired co-evolutionary algorithm with Tchebycheff decomposition (PICEA-g-td) is given. The performance of the proposed PICEA-g-td is evaluated by comparing it with NSGA-II, MOEA/D and PICEA-g. The experimental results show that the proposed algorithm performs better than the other three algorithms in terms of the solution quality. Finally, some useful management insights are obtained.https://ieeexplore.ieee.org/document/9605259/Epidemic logisticsrobust optimizationlocation-routing problemmulti-objective optimizationimproved heuristic algorithm |
| spellingShingle | Shengjie Long Dezhi Zhang Yijing Liang Shuangyan Li Wanru Chen Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand IEEE Access Epidemic logistics robust optimization location-routing problem multi-objective optimization improved heuristic algorithm |
| title | Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand |
| title_full | Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand |
| title_fullStr | Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand |
| title_full_unstemmed | Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand |
| title_short | Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand |
| title_sort | robust optimization of the multi objective multi period location routing problem for epidemic logistics system with uncertain demand |
| topic | Epidemic logistics robust optimization location-routing problem multi-objective optimization improved heuristic algorithm |
| url | https://ieeexplore.ieee.org/document/9605259/ |
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