Optimal Unit Commitment with Ant Colony Algorithm
نویسندگان
چکیده
منابع مشابه
Evolving ant colony optimization based unit commitment
Ant colony optimization (ACO) was inspired by the observation of natural behavior of real ants’ pheromone trail formation and foraging. Ant colony optimization ismore suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem. Multistage decision making of ACO gives an edge over other conventional methods. This paper proposes evolving ant col...
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Ant Colony Optimization is more suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem, and multistage decision making of ACO has an edge over other conventional methods. In this paper, the authors propose the Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) f...
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Ant colony optimization (ACO) which is inspired by the natural behavior of ants in finding the shortest path to food is appropriate for solving the combinatorial optimization problems. Therefore, it is used to solve the unit commitment problem (UCP) and attain the minimum cost for scheduling thermal units in order to produce the demand load. In this paper modified ACO (MACO) is used to solve th...
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In this paper, a cooperative metaheuristic for the solution of the Unit Commitment problem is presented. This problem is known to be a large scale, mixed integer problem. Due to combinatorial complexity, the exact solution is often intractable. Thus, a metaheuristic based method has to be used to compute a near optimal solution with low computation times. A new approach is presented here. The m...
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Ant Colony Optimization (ACO) is an optimization heuristic for solving combinatorial optimization problems and it is inspired by the swarming behavior of foraging ants. ACO has been successfully applied in various domains, such as routing and scheduling. In particular, the agents, called ants here, are very efficient at sampling the problem space and quickly finding good solutions. Motivated by...
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ژورنال
عنوان ژورنال: Computational Research
سال: 2014
ISSN: 2331-995X,2331-9984
DOI: 10.13189/cr.2014.020501