{"title":"应用启发式方法求解军用地面车辆车队规模问题","authors":"Dave C. Longhorn, John Dale Stobbs","doi":"10.1108/jdal-03-2020-0005","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to propose two solution approaches to determine the number of ground transport vehicles that are required to ensure the on-time delivery of military equipment between origin and destination node pairs in some geographic region, which is an important logistics problem at the US Transportation Command.\n\n\nDesign/methodology/approach\nThe author uses a mathematical program and a traditional heuristic to provide optimal and near-optimal solutions, respectively. The author also compares the approaches for random, small-scale problems to assess the quality and computational efficiency of the heuristic solution, and also uses the heuristic to solve a notional, large-scale problem typical of real problems.\n\n\nFindings\nThis work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.\n\n\nResearch limitations/implications\nThis research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.\n\n\nPractical implications\nThis work provides prescriptive details to military analysts and decision-makers in a timely manner. Prior to this work, insights for this type of problem were generated using time-consuming simulation taking about a week and often involving trial-and-error.\n\n\nOriginality/value\nThis research provides new methods to solve an important logistics problem. The heuristic presented in this paper was recently used to provide operational insights about ground vehicle requirements to support a geographic combatant command and to inform decisions for railcar recapitalization within the US Army.\n","PeriodicalId":32838,"journal":{"name":"Journal of Defense Analytics and Logistics","volume":"54 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A heuristic approach applied to the fleet sizing problem for military ground vehicles\",\"authors\":\"Dave C. Longhorn, John Dale Stobbs\",\"doi\":\"10.1108/jdal-03-2020-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis paper aims to propose two solution approaches to determine the number of ground transport vehicles that are required to ensure the on-time delivery of military equipment between origin and destination node pairs in some geographic region, which is an important logistics problem at the US Transportation Command.\\n\\n\\nDesign/methodology/approach\\nThe author uses a mathematical program and a traditional heuristic to provide optimal and near-optimal solutions, respectively. The author also compares the approaches for random, small-scale problems to assess the quality and computational efficiency of the heuristic solution, and also uses the heuristic to solve a notional, large-scale problem typical of real problems.\\n\\n\\nFindings\\nThis work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.\\n\\n\\nResearch limitations/implications\\nThis research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.\\n\\n\\nPractical implications\\nThis work provides prescriptive details to military analysts and decision-makers in a timely manner. Prior to this work, insights for this type of problem were generated using time-consuming simulation taking about a week and often involving trial-and-error.\\n\\n\\nOriginality/value\\nThis research provides new methods to solve an important logistics problem. The heuristic presented in this paper was recently used to provide operational insights about ground vehicle requirements to support a geographic combatant command and to inform decisions for railcar recapitalization within the US Army.\\n\",\"PeriodicalId\":32838,\"journal\":{\"name\":\"Journal of Defense Analytics and Logistics\",\"volume\":\"54 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Defense Analytics and Logistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/jdal-03-2020-0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Defense Analytics and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jdal-03-2020-0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Decision Sciences","Score":null,"Total":0}
A heuristic approach applied to the fleet sizing problem for military ground vehicles
Purpose
This paper aims to propose two solution approaches to determine the number of ground transport vehicles that are required to ensure the on-time delivery of military equipment between origin and destination node pairs in some geographic region, which is an important logistics problem at the US Transportation Command.
Design/methodology/approach
The author uses a mathematical program and a traditional heuristic to provide optimal and near-optimal solutions, respectively. The author also compares the approaches for random, small-scale problems to assess the quality and computational efficiency of the heuristic solution, and also uses the heuristic to solve a notional, large-scale problem typical of real problems.
Findings
This work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.
Research limitations/implications
This research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.
Practical implications
This work provides prescriptive details to military analysts and decision-makers in a timely manner. Prior to this work, insights for this type of problem were generated using time-consuming simulation taking about a week and often involving trial-and-error.
Originality/value
This research provides new methods to solve an important logistics problem. The heuristic presented in this paper was recently used to provide operational insights about ground vehicle requirements to support a geographic combatant command and to inform decisions for railcar recapitalization within the US Army.