A metaheuristic algorithm solving a Thermal Generator Maintenance Scheduling Problem

摘要

The maintenance scheduling of thermal generators is a large-scale combinatorial optimization problem with constraints. The effecfeve maintenance scheduling of thermal generators in a power system is very important to power utilities for economic and reliable operation of the power system. In this paper, a metaheuristic algorithm and specially an Ant System with elitist strategy (ASe) algorithm, one of the Ant Colony Optimization (ACO) algorithms, is proposed for the maintenance scheduling problem. This ant colony optimization method allows the "agents" of an ant colony to deposit a small amount of pheromone trail to every path that has been explored. With the iterations we construct the final solution. This method is called "positive feedback". The basic optimization routine is reinforced with the introduction of elitist ants who make the best solution stronger. The algorithm is applied to a real-scale system, and further experimenting leads to results that are commented. Comparison with the Max-Min Ant System algorithm and the Ant Colony System algorithm showed the superiority of the proposed Ant System with elitist strategy (ASe) algorithm.