Emergency Resource Layout Planning Methodology with Multiple Constraints
This paper first analyzes the characteristics and principles of the layout planning of emergency resources, explores the problems of emergency resource layout and distribution planning, and mentions the multi-constraint conditions of layout planning. Then, by describing the layout planning problem o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.01356 |
| _version_ | 1797340574099963904 |
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| author | Li Jing Zhao Lexin |
| author_facet | Li Jing Zhao Lexin |
| author_sort | Li Jing |
| collection | DOAJ |
| description | This paper first analyzes the characteristics and principles of the layout planning of emergency resources, explores the problems of emergency resource layout and distribution planning, and mentions the multi-constraint conditions of layout planning. Then, by describing the layout planning problem of emergency resources under multi-constraints and the related variable symbols, we constructed a two-layer layout planning model of emergency resources under multi-constraints, and after analyzing the particle swarm algorithm, we designed the layout planning model solving process based on particle swarm optimization. Finally, by constructing an emergency resource layout case, the centrality of the emergency resource layout network is explored, and the shortest distance and the best site selection of each emergency resource point corresponding to the demand point are divided. The results show that the structural degree centrality is between [0,0.78], the mileage degree centrality is between [0,1], the flow degree centrality is between [0.1,1], the structural median is between [0,0.32], the mileage median is between [0,2], and the structural proximity centrality and the mileage proximity centrality scores are both within the range of [0,1]. The shortest distribution distance of A, B, C, D, and E is selected to be only 393886m, and the error with the actual is around 0.009, which is able to carry out the layout planning effectively. |
| first_indexed | 2024-03-08T10:05:00Z |
| format | Article |
| id | doaj.art-c222b3e690b54ef4ae072a6444ca38fd |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:05:00Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-c222b3e690b54ef4ae072a6444ca38fd2024-01-29T08:52:42ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01356Emergency Resource Layout Planning Methodology with Multiple ConstraintsLi Jing0Zhao Lexin11School of Management, Xi’an University of Architecture and Technology, Xi’an, Shaanxi, 710055, China.1School of Management, Xi’an University of Architecture and Technology, Xi’an, Shaanxi, 710055, China.This paper first analyzes the characteristics and principles of the layout planning of emergency resources, explores the problems of emergency resource layout and distribution planning, and mentions the multi-constraint conditions of layout planning. Then, by describing the layout planning problem of emergency resources under multi-constraints and the related variable symbols, we constructed a two-layer layout planning model of emergency resources under multi-constraints, and after analyzing the particle swarm algorithm, we designed the layout planning model solving process based on particle swarm optimization. Finally, by constructing an emergency resource layout case, the centrality of the emergency resource layout network is explored, and the shortest distance and the best site selection of each emergency resource point corresponding to the demand point are divided. The results show that the structural degree centrality is between [0,0.78], the mileage degree centrality is between [0,1], the flow degree centrality is between [0.1,1], the structural median is between [0,0.32], the mileage median is between [0,2], and the structural proximity centrality and the mileage proximity centrality scores are both within the range of [0,1]. The shortest distribution distance of A, B, C, D, and E is selected to be only 393886m, and the error with the actual is around 0.009, which is able to carry out the layout planning effectively.https://doi.org/10.2478/amns.2023.2.01356multiple constraintstwo-tier layout planningparticle swarm algorithmemergency resource layoutdistribution planning91b32 |
| spellingShingle | Li Jing Zhao Lexin Emergency Resource Layout Planning Methodology with Multiple Constraints Applied Mathematics and Nonlinear Sciences multiple constraints two-tier layout planning particle swarm algorithm emergency resource layout distribution planning 91b32 |
| title | Emergency Resource Layout Planning Methodology with Multiple Constraints |
| title_full | Emergency Resource Layout Planning Methodology with Multiple Constraints |
| title_fullStr | Emergency Resource Layout Planning Methodology with Multiple Constraints |
| title_full_unstemmed | Emergency Resource Layout Planning Methodology with Multiple Constraints |
| title_short | Emergency Resource Layout Planning Methodology with Multiple Constraints |
| title_sort | emergency resource layout planning methodology with multiple constraints |
| topic | multiple constraints two-tier layout planning particle swarm algorithm emergency resource layout distribution planning 91b32 |
| url | https://doi.org/10.2478/amns.2023.2.01356 |
| work_keys_str_mv | AT lijing emergencyresourcelayoutplanningmethodologywithmultipleconstraints AT zhaolexin emergencyresourcelayoutplanningmethodologywithmultipleconstraints |