the major problem of wind turbines is the great variability of wind power production. the dynamic change of the wind speed returns the quantity of the power injected to networks. therefore, wind–thermal generation scheduling problem plays a key role to implement clean power producers in a competitive environment. in deregulated power systems, the scheduling problem has various objectives than i...

A hybrid algorithm by integrating an improved particle swarm optimization (IPSO) with successive quadratic programming (SQP), namely IPSO–SQP, is proposed for solving nonlinear optimal control problems. The particle swarm optimization (PSO) is showed to converge rapidly to a near optimum solution, but the search process will become very slow around global optimum. On the contrary, the ability o...

Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning periods. To improve the optimisation result of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisatio...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...

1. M.Basu, “Dynamic economic emission dispatch using non-dominated sorting genetic algorithm-II,” Electrical power and Energy systems 30 (2008) 140-149. 2. Li xuebin , “Study of multi-objective optimization and multi-attribute decision-making for dynamic economic emission dispatch,” Electric power components and systems, vol. 37: pp 1133-1148, 2009. 3. Elaiw A.M., Xia X,.Shehata A.M, “ Hydrid D...

In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

Due to many classical identification methods cannot be directly used for closed-loop control system, an improved identification method is proposed to simultaneously identify model parameters and the structure. The improved identification method used the genetic algorithm to estimate the initial search scope for the PSO algorithm, and then used the search result as the initial value of the Rosen...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradientbased algorithms can b...