A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Abstract

Abstract:In this paper, a gradient-based cuckoo search algorithm (GCS) is proposed to solve a reservoir-scheduling problem. The classical cuckoo search (CS) is first improved by a self-adaptive solution-generation technique, together with a differential strategy for Lévy flight. This improved CS is then employed to solve the reservoir-scheduling problem, and a two-way solution-correction strategy is introduced to handle variants' constraints. Moreover, a gradient-based search strategy is developed to improve the search speed and accuracy. Finally, the proposed GCS is used to obtain optimal schemes for cascade reservoirs in the Jinsha River, China. Results show that the mean and standard deviation of power generation obtained by GCS are much better than other methods. The converging speed of GCS is also faster. In the optimal results, the fluctuation of the water level obtained by GCS is small, indicating the proposed GCS's effectiveness in dealing with reservoir-scheduling problems.

Optimising models for prediction of tropospheric scintillation on satellite links

“…The CS optimisation algorithm is based on the parasitic and forced reproduction mechanism of some species of cuckoo birds, which lay their eggs in the nests of other birds (often other species), even expelling the eggs from the invaded nest to increase the probability that theirs will be born. If the host bird becomes aware that the egg is not its own, it will either kick the foreign egg out or abandon its nest and establish a new one, elsewhere [15][16][17]. The CS algorithm must comply with the following three basic rules [15]: (i) a global search process (known as diversification or exploration), in which each cuckoo bird will lay only one egg at a time, and choose the nest randomly, (ii) a local search process (known as intensification or exploitation), in which the best nests, i.e.…”

“…If the host bird becomes aware that the egg is not its own, it will either kick the foreign egg out or abandon its nest and establish a new one, elsewhere [15][16][17]. The CS algorithm must comply with the following three basic rules [15]: (i) a global search process (known as diversification or exploration), in which each cuckoo bird will lay only one egg at a time, and choose the nest randomly, (ii) a local search process (known as intensification or exploitation), in which the best nests, i.e. the best solutions, will advance to the next generation and (iii) the number of host nests is fixed, and an egg laid in a nest can be discovered by the host bird with an abandon probability, p a ∈ [0,1].…”

“…In (2), it is important to emphasise that, if p a < r 1 , then H p a − r 1 = 0, and, consequently, x k+1 i = x k i . For the global search, in the CS algorithm is used Lévy flight [15,16] x k+1…”

“…For the global search, in the CS algorithm is used Lévy flight [15, 16] where β is the distribution factor.…”

“…In this sense, in this work, measurements of tropospheric scintillation reported from Spain [14] will be used to obtain new models for the prediction of the scintillation. For the development of the models, existing models will be optimised, more specifically, those mentioned above, using the computational intelligence technique Cuckoo Search (CS) [15][16][17], aiming to the minimisation of root mean square error (RMSE) existing between the estimated values by the optimised models and the measured values.…”