{"title":"具有时间窗的大型加油站补给问题:一个真实案例研究","authors":"Pablo A. Villegas, V. M. Albornoz","doi":"10.5220/0005823604080415","DOIUrl":null,"url":null,"abstract":"In this study we deal with a real case of the problem known as Petrol Station Replenishment Problem with Time Windows arising in Chile. The company involved is one of the biggest actors in the country, and every day must schedule a series of trips from their depots to their clients, delivering different kinds of fuel. This specific case has some differences from prior formulations of this problem (e.g. trucks works in shifts with hard time windows). Also, another challenge is the high number of orders and trucks involved in everyday planning. To solve this problem in reasonable computing times we propose a sequential insertion heuristic. Finally, we present results over a month of data.","PeriodicalId":235376,"journal":{"name":"International Conference on Operations Research and Enterprise Systems","volume":"178 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large Scale Petrol Station Replenishment Problem with Time Windows: A Real Case Study\",\"authors\":\"Pablo A. Villegas, V. M. Albornoz\",\"doi\":\"10.5220/0005823604080415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study we deal with a real case of the problem known as Petrol Station Replenishment Problem with Time Windows arising in Chile. The company involved is one of the biggest actors in the country, and every day must schedule a series of trips from their depots to their clients, delivering different kinds of fuel. This specific case has some differences from prior formulations of this problem (e.g. trucks works in shifts with hard time windows). Also, another challenge is the high number of orders and trucks involved in everyday planning. To solve this problem in reasonable computing times we propose a sequential insertion heuristic. Finally, we present results over a month of data.\",\"PeriodicalId\":235376,\"journal\":{\"name\":\"International Conference on Operations Research and Enterprise Systems\",\"volume\":\"178 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Operations Research and Enterprise Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0005823604080415\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Operations Research and Enterprise Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005823604080415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large Scale Petrol Station Replenishment Problem with Time Windows: A Real Case Study
In this study we deal with a real case of the problem known as Petrol Station Replenishment Problem with Time Windows arising in Chile. The company involved is one of the biggest actors in the country, and every day must schedule a series of trips from their depots to their clients, delivering different kinds of fuel. This specific case has some differences from prior formulations of this problem (e.g. trucks works in shifts with hard time windows). Also, another challenge is the high number of orders and trucks involved in everyday planning. To solve this problem in reasonable computing times we propose a sequential insertion heuristic. Finally, we present results over a month of data.