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In this paper we look at a new hybrid Genetic Algorithm (HGA) based on genetic simulated annealing (GSA) algorithm for solving heat exchanger network synthesis (HENS) problems with Mixed Integer Nonlinear Programming (MINLP) model. In order to efficiently locate quality solution to complex optimization problem, a self-adaptive mechanism is developed to maintain a tradeoff between the global and local...
In this paper we presented a novel hybrid genetic algorithm for solving NLP problems based on combining the Genetic algorithm and Simulated annealing, together with a local search strategy. The proposed hybrid approach combines the merits of genetic algorithm (GA) with simulated annealing (SA) to construct a more efficient genetic simulated annealing (GSA) algorithm for global search, which could...
A pragmatic hybrid genetic algorithm named parallel adaptive genetic simulated annealing (PAGSA) is developed. The proposed hybrid approach combines the merits of genetic algorithm (GA) with simulated annealing (SA) to construct a more efficient genetic simulated annealing (GSA) algorithm for global search, while the iterative hill climbing (IHC) method is used as a local search technique to incorporate...
A new approach about design of controller (GL) for integrated self-adaptive genetic annealing algorithm (SGAA) and sliding mode control (SGAA-SMC) was proposed in this study. The main objective of this paper is to improve the non-minimum phase system performance by continuously updating the parameters of the sliding surface by SGAA. Firstly, Based on traditional fuzzy logic sliding mode control (FLSMC),...
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