{"title":"解决泊位- qc分配问题的综合优化方法","authors":"Meilong Le, Cong-cong Wu, Hong Zhang","doi":"10.1109/ICNC.2012.6234544","DOIUrl":null,"url":null,"abstract":"This paper aims to use optimization method to solve the Berth-Quay Crane Allocation Problem. The objective used here is to minimize the total stevedoring time and the total operational cost. In order to solve the problem in reasonable time, the multi-objective Particle Swarm Optimization (PSO) method is designed. Five instances with 30, 40, 50, 60, 70 ships are used for testing the model and PSO. The result of experimental computations indicate that the algorithm is effective and the model can get the optimal trade-off solution between time and cost. Compared with the single-objective model, the multi-objective model is more beneficial to the whole shipping system.","PeriodicalId":404981,"journal":{"name":"2012 8th International Conference on Natural Computation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An integrated optimization method to solve the berth-QC allocation problem\",\"authors\":\"Meilong Le, Cong-cong Wu, Hong Zhang\",\"doi\":\"10.1109/ICNC.2012.6234544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims to use optimization method to solve the Berth-Quay Crane Allocation Problem. The objective used here is to minimize the total stevedoring time and the total operational cost. In order to solve the problem in reasonable time, the multi-objective Particle Swarm Optimization (PSO) method is designed. Five instances with 30, 40, 50, 60, 70 ships are used for testing the model and PSO. The result of experimental computations indicate that the algorithm is effective and the model can get the optimal trade-off solution between time and cost. Compared with the single-objective model, the multi-objective model is more beneficial to the whole shipping system.\",\"PeriodicalId\":404981,\"journal\":{\"name\":\"2012 8th International Conference on Natural Computation\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 8th International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2012.6234544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 8th International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2012.6234544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An integrated optimization method to solve the berth-QC allocation problem
This paper aims to use optimization method to solve the Berth-Quay Crane Allocation Problem. The objective used here is to minimize the total stevedoring time and the total operational cost. In order to solve the problem in reasonable time, the multi-objective Particle Swarm Optimization (PSO) method is designed. Five instances with 30, 40, 50, 60, 70 ships are used for testing the model and PSO. The result of experimental computations indicate that the algorithm is effective and the model can get the optimal trade-off solution between time and cost. Compared with the single-objective model, the multi-objective model is more beneficial to the whole shipping system.