A comparison of three metaheuristics for the workover rig routing problem

详细信息	查看全文 | 推荐本文 |

• 作者：Glaydston Mattos Ribeiro^a ; ^b ; ^{glaydstonribeiro@ceunes.ufes.br} ; Gilbert Laporte^a ; ^{gilbert.laporte@cirrelt.ca} ; Geraldo Regis Mauri^c ; ^{mauri@cca.ufes.br}
• 关键词：Metaheuristics ; Iterated local search ; Clustering search ; Adaptive large neighborhood search ; Workover rig routing problem
• 刊名：European Journal of Operational Research
• 出版年：2012
• 期刊代码：58_03772217
• 类别：et
• 出版时间：1 July, 2012
• 卷：220
• 期：1
• 页码：28-36
• 文件大小：833 K

摘要

The workover rig routing problem (WRRP) is a variant of the Vehicle Routing Problem with Time Windows (VRPTW) and arises in the operations of onshore oil fields. In this problem, a set of workover rigs located at different positions must service oil wells requesting maintenance as soon as possible. When a well requires maintenance, its production is reduced or stopped for safety reasons and some workover rig must service it within a given deadline. It is therefore important to service the wells in a timely fashion in order to minimize the production loss. Whereas for classical VRPTWs the objective is to minimize route length, in the WRRP the objective is to minimize the total lost production, equal to the sum of arrival times at the wells, multiplied by production loss rates. The WRRP generalizes the Delivery Man Problem with Time Windows by considering multiple open vehicle routes and multiple depots. This paper compares three metaheuristics for the WRRP: an iterated local search, a clustering search, and an Adaptive Large Neighborhood Search (ALNS). All approaches, in particular ALNS, have yielded good solutions for instances derived from a real-life setting.