Optimal allocation model of port emergency resources based on the improved multi-objective particle swarm algorithm and TOPSIS method
The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for...
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| Vydané v: | Marine pollution bulletin Ročník 209; číslo Pt B; s. 117214 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
Elsevier Ltd
01.12.2024
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| ISSN: | 0025-326X, 1879-3363, 1879-3363 |
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| Abstract | The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters.
•An optimal allocation model based on IMOPSO and entropy weighted TOPSIS has been proposed for port emergency resources.•The MOPSO algorithm was further improved and its performance was quantitatively evaluated.•A case study of oil spill dispersant allocation was conducted at Zhanjiang Port and the model effectiveness was verified.•The optimal scheme determined by entropy-weighted TOPSIS would provide a guidance for marine environmental management. |
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| AbstractList | The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters. The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters. •An optimal allocation model based on IMOPSO and entropy weighted TOPSIS has been proposed for port emergency resources.•The MOPSO algorithm was further improved and its performance was quantitatively evaluated.•A case study of oil spill dispersant allocation was conducted at Zhanjiang Port and the model effectiveness was verified.•The optimal scheme determined by entropy-weighted TOPSIS would provide a guidance for marine environmental management. The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters. The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters.The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters. |
| ArticleNumber | 117214 |
| Author | Jiang, Zhonglian Zheng, Fengfan Ying, Jianglong Feng, Xuejun Guo, Jianqun |
| Author_xml | – sequence: 1 givenname: Jianqun surname: Guo fullname: Guo, Jianqun organization: State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China – sequence: 2 givenname: Zhonglian surname: Jiang fullname: Jiang, Zhonglian email: z.jiang@whut.edu.cn organization: State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China – sequence: 3 givenname: Jianglong surname: Ying fullname: Ying, Jianglong organization: State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China – sequence: 4 givenname: Xuejun surname: Feng fullname: Feng, Xuejun organization: Institute of Maritime Logistics and Green Development, Hohai University, Nanjing 210098, China – sequence: 5 givenname: Fengfan surname: Zheng fullname: Zheng, Fengfan organization: Wuhan Rules and Research Institute, China Classification Society, Wuhan 430022, China |
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| Keywords | NSGA-II Multi-objective optimization Entropy-weighted TOPSIS Improved particle swarm algorithm Emergency resource allocation |
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| SubjectTerms | Algorithms case studies China dispersants Emergency resource allocation Entropy-weighted TOPSIS environmental management Improved particle swarm algorithm marine pollution Models, Theoretical Multi-objective optimization mutation NSGA-II oil spills Petroleum Pollution pollutants Resource Allocation sea transportation Ships |
| Title | Optimal allocation model of port emergency resources based on the improved multi-objective particle swarm algorithm and TOPSIS method |
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