{"title":"动态团队定向问题","authors":"Emre Kirac , Ashlea Bennett Milburn , Ridvan Gedik","doi":"10.1016/j.ejor.2025.01.009","DOIUrl":null,"url":null,"abstract":"<div><div>This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within a time limit. This problem arises in several practical applications such as disaster relief, technician, tourist, and school bus routing problems. We adopt a Multiple Plan Approach (MPA) to solve the proposed problem, utilizing both a consensus function method and a demand-served method to select the distinguished plan—the most promising solution from a pool of alternative routing plans. To assess the effectiveness of these methods, we employ a sophisticated greedy algorithm tailored to address the unique challenges posed by the DTOP. In addition, we employ a reference offline algorithm designed for solving the static variant of the problem. To facilitate our evaluation, we introduce a comprehensive set of 1161 new benchmark instances for the DTOP, adapted from well-established TOP benchmark instances. Our comparative analysis centers on the average percentage deviation of algorithmic solutions from the reference offline solutions.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"324 1","pages":"Pages 22-39"},"PeriodicalIF":6.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Dynamic Team Orienteering Problem\",\"authors\":\"Emre Kirac , Ashlea Bennett Milburn , Ridvan Gedik\",\"doi\":\"10.1016/j.ejor.2025.01.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within a time limit. This problem arises in several practical applications such as disaster relief, technician, tourist, and school bus routing problems. We adopt a Multiple Plan Approach (MPA) to solve the proposed problem, utilizing both a consensus function method and a demand-served method to select the distinguished plan—the most promising solution from a pool of alternative routing plans. To assess the effectiveness of these methods, we employ a sophisticated greedy algorithm tailored to address the unique challenges posed by the DTOP. In addition, we employ a reference offline algorithm designed for solving the static variant of the problem. To facilitate our evaluation, we introduce a comprehensive set of 1161 new benchmark instances for the DTOP, adapted from well-established TOP benchmark instances. Our comparative analysis centers on the average percentage deviation of algorithmic solutions from the reference offline solutions.</div></div>\",\"PeriodicalId\":55161,\"journal\":{\"name\":\"European Journal of Operational Research\",\"volume\":\"324 1\",\"pages\":\"Pages 22-39\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Operational Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377221725000347\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Operational Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377221725000347","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within a time limit. This problem arises in several practical applications such as disaster relief, technician, tourist, and school bus routing problems. We adopt a Multiple Plan Approach (MPA) to solve the proposed problem, utilizing both a consensus function method and a demand-served method to select the distinguished plan—the most promising solution from a pool of alternative routing plans. To assess the effectiveness of these methods, we employ a sophisticated greedy algorithm tailored to address the unique challenges posed by the DTOP. In addition, we employ a reference offline algorithm designed for solving the static variant of the problem. To facilitate our evaluation, we introduce a comprehensive set of 1161 new benchmark instances for the DTOP, adapted from well-established TOP benchmark instances. Our comparative analysis centers on the average percentage deviation of algorithmic solutions from the reference offline solutions.
期刊介绍:
The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.