Efficient heuristics for the workover rig routing problem with a heterogeneous fleet and a finite horizon
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Author(s)
Ribeiro, Glaydston Mattos
Desaulniers, Guy
Desrosiers, Jacques
Vidal, Thibaut
Vieira, Bruno Salezze
Date Issued
September 2014
Journal
Journal of Heuristics
Publisher
Springer US
Citation
Ribeiro, Glaydston Mattos et al. “Efficient Heuristics for the Workover Rig Routing Problem with a Heterogeneous Fleet and a Finite Horizon.” Journal of Heuristics 20.6 (2014): 677–708.
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Author's final manuscript
Abstract
Onshore oil fields may contain hundreds of wells that use sophisticated and complex equipments. These equipments need regular maintenance to keep the wells at maximum productivity. When the productivity of a well decreases, a specially-equipped vehicle called a workover rig must visit this well to restore its full productivity. Given a heterogeneous fleet of workover rigs and a set of wells requiring maintenance, the workover rig routing problem (WRRP) consists of finding rig routes that minimize the total production loss of the wells over a finite horizon. The wells have different loss rates, need different services, and may not be serviced within the horizon. On the other hand, the number of available workover rigs is limited, they have different initial positions, and they do not have the same equipments. This paper presents and compares four heuristics for the WRRP: an existing variable neighborhood search heuristic, a branch-price-and-cut heuristic, an adaptive large neighborhood search heuristic, and a hybrid genetic algorithm. These heuristics are tested on practical-sized instances involving up to 300 wells, 10 rigs on a 350-period horizon. Our computational results indicate that the hybrid genetic algorithm outperforms the other heuristics on average and in most cases.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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DOI of Published Version
https://doi.org/10.1007/s10732-014-9262-1
