Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm
With the continuous prosperity and development of the shipping industry, it is necessary and meaningful to plan a safe, green, and efficient route for ships sailing far away. In this study, a hybrid multicriteria ship route planning method based on improved particle swarm optimization–genetic algori...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/9/4/357 |
| _version_ | 1797540027355365376 |
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| author | Wei Zhao Yan Wang Zhanshuo Zhang Hongbo Wang |
| author_facet | Wei Zhao Yan Wang Zhanshuo Zhang Hongbo Wang |
| author_sort | Wei Zhao |
| collection | DOAJ |
| description | With the continuous prosperity and development of the shipping industry, it is necessary and meaningful to plan a safe, green, and efficient route for ships sailing far away. In this study, a hybrid multicriteria ship route planning method based on improved particle swarm optimization–genetic algorithm is presented, which aims to optimize the meteorological risk, fuel consumption, and navigation time associated with a ship. The proposed algorithm not only has the fast convergence of the particle swarm algorithm but also improves the diversity of solutions by applying the crossover operation, selection operation, and multigroup elite selection operation of the genetic algorithm and improving the Pareto optimal frontier distribution. Based on the Pareto optimal solution set obtained by the algorithm, the minimum-navigation-time route, the minimum-fuel-consumption route, the minimum-navigation-risk route, and the recommended route can be obtained. Herein, a simulation experiment is conducted with respect to a container ship, and the optimization route is compared and analyzed. Experimental results show that the proposed algorithm can plan a series of feasible ship routes to ensure safety, greenness, and economy and that it provides route selection references for captains and shipping companies. |
| first_indexed | 2024-03-10T12:54:13Z |
| format | Article |
| id | doaj.art-6ba10735629644349d48eb0053762e4b |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T12:54:13Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-6ba10735629644349d48eb0053762e4b2023-11-21T12:03:22ZengMDPI AGJournal of Marine Science and Engineering2077-13122021-03-019435710.3390/jmse9040357Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic AlgorithmWei Zhao0Yan Wang1Zhanshuo Zhang2Hongbo Wang3State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130000, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130000, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130000, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130000, ChinaWith the continuous prosperity and development of the shipping industry, it is necessary and meaningful to plan a safe, green, and efficient route for ships sailing far away. In this study, a hybrid multicriteria ship route planning method based on improved particle swarm optimization–genetic algorithm is presented, which aims to optimize the meteorological risk, fuel consumption, and navigation time associated with a ship. The proposed algorithm not only has the fast convergence of the particle swarm algorithm but also improves the diversity of solutions by applying the crossover operation, selection operation, and multigroup elite selection operation of the genetic algorithm and improving the Pareto optimal frontier distribution. Based on the Pareto optimal solution set obtained by the algorithm, the minimum-navigation-time route, the minimum-fuel-consumption route, the minimum-navigation-risk route, and the recommended route can be obtained. Herein, a simulation experiment is conducted with respect to a container ship, and the optimization route is compared and analyzed. Experimental results show that the proposed algorithm can plan a series of feasible ship routes to ensure safety, greenness, and economy and that it provides route selection references for captains and shipping companies.https://www.mdpi.com/2077-1312/9/4/357multicriteria route planninggenetic algorithmparticle swarm optimizationoceanic meteorological routing |
| spellingShingle | Wei Zhao Yan Wang Zhanshuo Zhang Hongbo Wang Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm Journal of Marine Science and Engineering multicriteria route planning genetic algorithm particle swarm optimization oceanic meteorological routing |
| title | Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm |
| title_full | Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm |
| title_fullStr | Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm |
| title_full_unstemmed | Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm |
| title_short | Multicriteria Ship Route Planning Method Based on Improved Particle Swarm Optimization–Genetic Algorithm |
| title_sort | multicriteria ship route planning method based on improved particle swarm optimization genetic algorithm |
| topic | multicriteria route planning genetic algorithm particle swarm optimization oceanic meteorological routing |
| url | https://www.mdpi.com/2077-1312/9/4/357 |
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