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- W2015195622 abstract "This investigation proposes a new algorithm for the solution of multi-objective, short-term hydrothermal scheduling problems. In the common algorithm using weighting method, a set of weight vectors are fed infor each weight vector objective function values in the optimisation interval, and the corresponding fuzzy membership functions are computed and the best compromise solution is identified from the set of non-inferior solutions obtained. In the proposed algorithm, a set of weight vectors are genetically generated and the best solution is identified as described already. Further, the weight vectors are genetically modified and the process is repeated to identify the best solution using the modified weight vectors. The process is continued till change in the fitness value of the best solution is marginal. The investigation further proposes three methods to determine the objective function values in the optimisation interval, which is a major sub-process in the above algorithm. These are the Newton-Raphson method, a genetic search method and a random search method. A comparison is made among the performance data of the three methods, and the random search method is projected as the simple algorithm for multi-objective, short-term hydrothermal scheduling problem. A coal-constrained thermal unit is introduced in the investigation to make the scheduling problem more universal." @default.
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- W2015195622 date "2012-01-01" @default.
- W2015195622 modified "2023-09-26" @default.
- W2015195622 title "A Simple Algorithm for Multi-Objective, Short-Term Hydrothermal Scheduling" @default.
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- W2015195622 doi "https://doi.org/10.1080/1448837x.2012.11464340" @default.
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