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This paper presents a fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solving the large economic power dispatch with non-smooth cost fuel functions. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules, the adaptive PSO executed in parallel based in decomposed network procedure as a local search...
This paper describes secant method with particle swarm optimization (PSO) for solving the economic dispatch (ED) problem with valve point loading. The ED problem is solved in two stages. The range of output powers near the global optimal solution is determined by the secant method and then the final optimal solution is obtained by PSO. The proposed algorithm has been tested on 3-, 13- and 40-units...
This paper describes secant method combined with particle swarm optimization for solving economic dispatch (ED) problem with prohibited operating zones. Two stages are involved in the proposed approach to solve the ED problem with prohibited operating zones. First, the range of output powers near to the global optimal solution is determined by secant method without considering prohibited zones and...
Some problems are known to have computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs portfolio of intelligent systems algorithms for optimising a metal reheat furnace scheduling problem. The proposed system has been evaluated for different techniques...
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