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

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.

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

2010 ◽  
Vol 1 (2) ◽  
pp. 1-14 ◽  
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.

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

2020 ◽  
Vol 37 (6) ◽  
Author(s):  
Sergio Pérez‐Peló ◽  
Jesús Sánchez‐Oro ◽  
Abraham Duarte
Keyword(s):  
Path Relinking ◽  
Search Procedure ◽  
Adaptive Search

Greedy randomized adaptive search procedure with exterior path relinking for differential dispersion minimization

2015 ◽  
Vol 296 ◽  
pp. 46-60 ◽  
Author(s):  
Abraham Duarte ◽  
Jesús Sánchez-Oro ◽  
Mauricio G.C. Resende ◽  
Fred Glover ◽  
Rafael Martí
Keyword(s):  
Path Relinking ◽  
Search Procedure ◽  
Adaptive Search

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

2017 ◽  
Vol 32 (6) ◽  
pp. 1319-1334 ◽  
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

scholarly journals A Heuristic Procedure for a Ship Routing and Scheduling Problem with Variable Speed and Discretized Time Windows

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Krystel K. Castillo-Villar ◽  
Rosa G. González-Ramírez ◽  
Pablo Miranda González ◽  
Neale R. Smith
Keyword(s):  
Time Windows ◽  
Waiting Times ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Computational Results ◽  
Solution Quality ◽  
Ship Routing ◽  
Routing And Scheduling ◽  
Ship Routing And Scheduling ◽  
Tramp Shipping

This paper develops a heuristic algorithm for solving a routing and scheduling problem for tramp shipping with discretized time windows. The problem consists of determining the set of cargoes that should be served by each ship, the arrival, departure, and waiting times at each port, while minimizing total costs. The heuristic proposed is based on a variable neighborhood search, considering a number of neighborhood structures to find a solution to the problem. We present computational results, and, for comparison purposes, we consider instances that can be solved directly by CPLEX to test the performance of the proposed heuristic. The heuristics achieves good solution quality with reasonable computational times. Our computational results are encouraging and establish that our heuristic can be utilized to solve large real-size instances.

scholarly journals Dynamic scheduling with cancellations: an application to chemotherapy appointment booking

2018 ◽  
Vol 8 (2) ◽  
pp. 161-169
Author(s):  
Yasin Göçgün
Keyword(s):  
Decision Process ◽  
Approximate Dynamic Programming ◽  
Dynamic Scheduling ◽  
Time Windows ◽  
Scheduling Problem ◽  
Computational Results ◽  
Due Dates ◽  
Different Types ◽  
Markov Decision ◽  
Myopic Policy

We study a dynamic scheduling problem that has the feature of due dates and time windows. This problem arises in chemotherapy scheduling where patients from different types have specific target dates along with time windows for appointment. We consider cancellation of appointments. The problem is modeled as a Markov Decision Process (MDP) and approximately solved using a direct-search based approximate dynamic programming (ADP) tehnique. We compare the performance of the ADP technique against the myopic policy under diverse scenarios. Our computational results reveal that the ADP technique outperforms the myopic policy on majority of problem sets we generated.

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