{"title":"重新考虑紧凑措施:生态保护区设计的多目标框架","authors":"Nathan Adelgren , Lakmali Weerasena , Damitha Bandara","doi":"10.1016/j.cor.2025.107241","DOIUrl":null,"url":null,"abstract":"<div><div>This study aims to develop a refined compactness measure, a key spatial attribute in reserve design that impacts both ecological and economic efficiency. Designing ecological reserves often involves conflicting objectives, necessitating the simultaneous consideration of spatial attribute and ecological diversity. We introduce a novel metric that accounts for both size and shape in measuring reserve compactness. Additionally, we employ multiobjective optimization to generate Pareto-optimal solutions, offering stakeholders a range of high-quality reserve configurations. Our focus on compactness is particularly relevant when clusters represent distinct habitats with limited biological interactions. We compare various compactness measures, such as boundary length and pairwise distance and evaluate their suitability for inclusion in optimization models. This approach addresses diverse stakeholder priorities, leading to more balanced reserve selections. We demonstrate the shortcomings of single-objective approaches, which often yield suboptimal, non-compact reserves, and highlight the advantages of optimizing across multiple metrics to better capture the complexities of reserve design.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"184 ","pages":"Article 107241"},"PeriodicalIF":4.3000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconsidering compact measures: A multiobjective framework for ecological reserve design\",\"authors\":\"Nathan Adelgren , Lakmali Weerasena , Damitha Bandara\",\"doi\":\"10.1016/j.cor.2025.107241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study aims to develop a refined compactness measure, a key spatial attribute in reserve design that impacts both ecological and economic efficiency. Designing ecological reserves often involves conflicting objectives, necessitating the simultaneous consideration of spatial attribute and ecological diversity. We introduce a novel metric that accounts for both size and shape in measuring reserve compactness. Additionally, we employ multiobjective optimization to generate Pareto-optimal solutions, offering stakeholders a range of high-quality reserve configurations. Our focus on compactness is particularly relevant when clusters represent distinct habitats with limited biological interactions. We compare various compactness measures, such as boundary length and pairwise distance and evaluate their suitability for inclusion in optimization models. This approach addresses diverse stakeholder priorities, leading to more balanced reserve selections. We demonstrate the shortcomings of single-objective approaches, which often yield suboptimal, non-compact reserves, and highlight the advantages of optimizing across multiple metrics to better capture the complexities of reserve design.</div></div>\",\"PeriodicalId\":10542,\"journal\":{\"name\":\"Computers & Operations Research\",\"volume\":\"184 \",\"pages\":\"Article 107241\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Operations Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0305054825002709\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054825002709","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Reconsidering compact measures: A multiobjective framework for ecological reserve design
This study aims to develop a refined compactness measure, a key spatial attribute in reserve design that impacts both ecological and economic efficiency. Designing ecological reserves often involves conflicting objectives, necessitating the simultaneous consideration of spatial attribute and ecological diversity. We introduce a novel metric that accounts for both size and shape in measuring reserve compactness. Additionally, we employ multiobjective optimization to generate Pareto-optimal solutions, offering stakeholders a range of high-quality reserve configurations. Our focus on compactness is particularly relevant when clusters represent distinct habitats with limited biological interactions. We compare various compactness measures, such as boundary length and pairwise distance and evaluate their suitability for inclusion in optimization models. This approach addresses diverse stakeholder priorities, leading to more balanced reserve selections. We demonstrate the shortcomings of single-objective approaches, which often yield suboptimal, non-compact reserves, and highlight the advantages of optimizing across multiple metrics to better capture the complexities of reserve design.
期刊介绍:
Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.