scholarly journals Production and Maintenance Scheduling Supported by Genetic Algorithms

2018 ◽  
pp. 49-59
Author(s):  
Duarte Alemão ◽  
Mafalda Parreira-Rocha ◽  
José Barata
Keyword(s):  
Genetic Algorithms ◽  
Maintenance Scheduling

Optimal Generator Maintenance Scheduling Using a Hybrid Metaheuristic Approach

2015 ◽  
Vol 14 (02) ◽  
pp. 1550011 ◽  
Author(s):  
N. Bali ◽  
H. Labdelaoui
Keyword(s):  
Genetic Algorithms ◽  
Hybrid Approach ◽  
Test System ◽  
Maintenance Scheduling ◽  
The Other ◽  
Optimization Approach ◽  
Control Parameters ◽  
Hybrid Metaheuristic ◽  
Reliability Performance ◽  
Optimal Approach

This paper presents an optimal approach for solving the generator maintenance scheduling (GMS) problem using a hybrid metaheuristic-based method. The GMS problem is formulated mathematically as a minimization problem of an aggregated objective function that handles both the reliability performance and the constraints violations. A new optimization approach, based on simulated annealing (SA) and ant colony optimization (ACO) is proposed to solve this problem. The optimization results for a 21-unit test system show that the proposed hybrid approach is more efficient than the standard SA and ACO methods and also genetic algorithms (GAs). It is also shown that the proposed approach is less sensitive to the variations of some control parameters and is more reliable than the other approaches.

Genetic algorithms solution to generator maintenance scheduling with modified genetic operators

2003 ◽  
Vol 150 (1) ◽  
pp. 56 ◽  
Author(s):  
S. Baskar ◽  
P. Subbaraj ◽  
M.V.C. Rao ◽  
S. Tamilselvi
Keyword(s):  
Genetic Algorithms ◽  
Maintenance Scheduling ◽  
Genetic Operators

Genetic Algorithms—a Tool for OR?

1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  
Genetic Algorithms
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