{"title":"多技能资源约束项目调度问题的新基准数据集","authors":"P. Myszkowski, Marek Skowronski, Krzysztof Sikora","doi":"10.15439/2015F273","DOIUrl":null,"url":null,"abstract":"In this paper novel project scheduling difficulty estimations are proposed for Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). The main goal of introducing the complexity estimations is an attempt of estimation the project complexity before launching the optimization process. What is more, the dataset instance generator is also presented as a tool to create new instances for extending the research area. Furthermore, the dataset proposed in previous works is extended by new instances, described thoroughly and released as a benchmark dataset. The dataset instances are also scheduled using simple heuristic and greedy algorithm in duration- and cost- oriented optimization modes. Finally, a brief summary of investigated methods and potential further research directions is presented.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"A new benchmark dataset for Multi-Skill Resource-Constrained Project Scheduling Problem\",\"authors\":\"P. Myszkowski, Marek Skowronski, Krzysztof Sikora\",\"doi\":\"10.15439/2015F273\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper novel project scheduling difficulty estimations are proposed for Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). The main goal of introducing the complexity estimations is an attempt of estimation the project complexity before launching the optimization process. What is more, the dataset instance generator is also presented as a tool to create new instances for extending the research area. Furthermore, the dataset proposed in previous works is extended by new instances, described thoroughly and released as a benchmark dataset. The dataset instances are also scheduled using simple heuristic and greedy algorithm in duration- and cost- oriented optimization modes. Finally, a brief summary of investigated methods and potential further research directions is presented.\",\"PeriodicalId\":276884,\"journal\":{\"name\":\"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15439/2015F273\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2015F273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new benchmark dataset for Multi-Skill Resource-Constrained Project Scheduling Problem
In this paper novel project scheduling difficulty estimations are proposed for Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). The main goal of introducing the complexity estimations is an attempt of estimation the project complexity before launching the optimization process. What is more, the dataset instance generator is also presented as a tool to create new instances for extending the research area. Furthermore, the dataset proposed in previous works is extended by new instances, described thoroughly and released as a benchmark dataset. The dataset instances are also scheduled using simple heuristic and greedy algorithm in duration- and cost- oriented optimization modes. Finally, a brief summary of investigated methods and potential further research directions is presented.