A Seeded Memetic Algorithm for Large Unit Commitment Problems
Journal of Heuristics
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
A binary-real-coded differential evolution for unit commitment problem: a preliminary study
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
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The Unit Commitment Problem (UCP) is the task of finding an optimal turn on and turn off schedule for a group of power generation units over a given time horizon to minimize operation costs while satisfying the hourly power demand constraints. Various approaches exist in the literature for solving this problem. This paper reports the results of experiments performed on a series of the UCP test data using the binary differential evolution approach combined with a simple local search mechanism. In the future stages of the project, the algorithm will be applied to solve the UCP for the Turkish interconnected power system.