Finding weaknesses in networks using Greedy Randomized Adaptive Search Procedure and Path Relinking

Onshore oil wells depend on special services like cleaning, reinstatement and stimulation. These services, which are performed by a short number of workover rigs, are important to keep oil production as optimum as possible. Consequently, scheduling must be determined, where several factors interfere, such as production, service to be performed on each well, and time windows for each service. When a well needs service, its production is interrupted. In this regard, the workover rig scheduling problem consists of finding the best sequence of wells, which minimizes the production loss associated with the wells waiting for maintenance. In this paper, the authors present a Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) to solve this problem. Computational results are obtained from real problems of a Brazilian oil field.

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Greedy Randomized Adaptive Search Procedure with Path-Relinking for the Vertex p-Center Problem

Journal of Computer Science and Technology ◽

10.1007/s11390-017-1802-3 ◽

2017 ◽

Vol 32 (6) ◽

pp. 1319-1334 ◽

Cited By ~ 2

Author(s):

Ai-Hua Yin ◽

Tao-Qing Zhou ◽

Jun-Wen Ding ◽

Qing-Jie Zhao ◽

Zhi-Peng Lv

Keyword(s):

Path Relinking ◽

Search Procedure ◽

Adaptive Search ◽

Center Problem

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A Grasp with Path-Relinking for the Workover Rig Scheduling Problem

Nature-Inspired Computing Design, Development, and Applications ◽

10.4018/978-1-4666-1574-8.ch005 ◽

2012 ◽

pp. 90-103

Author(s):

Alexandre Venturin Faccin Pacheco ◽

Glaydston Mattos Ribeiro ◽

Geraldo Regis Mauri

Keyword(s):

Time Windows ◽

Oil Wells ◽

Oil Field ◽

Path Relinking ◽

Scheduling Problem ◽

Search Procedure ◽

Computational Results ◽

Production Loss ◽

Adaptive Search ◽

Special Services

Onshore oil wells depend on special services like cleaning, reinstatement and stimulation. These services, which are performed by a short number of workover rigs, are important to keep oil production as optimum as possible. Consequently, scheduling must be determined, where several factors interfere, such as production, service to be performed on each well, and time windows for each service. When a well needs service, its production is interrupted. In this regard, the workover rig scheduling problem consists of finding the best sequence of wells, which minimizes the production loss associated with the wells waiting for maintenance. In this paper, the authors present a Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) to solve this problem. Computational results are obtained from real problems of a Brazilian oil field.

Download Full-text