This research deals with the synthesis of control law by means of Analytic Programming (AP) for the Hénon Map, which is discrete chaotic system. The tool for symbolic regression (AP) is used for the purpose of stabilization of stable state and higher periodic orbits, which represent oscillations between several values of chaotic system. For experimentation, Self-Organizing Migrating Algorithm (...

This paper deals with synthesizing control laws by means of analytic programming (AP) for the Hénon map, which is a discrete chaotic system. The tool for symbolic regression is used for stabilizing the stable state and higher periodic orbits, which represent oscillations between several values of a chaotic system. For experimentation, the self-organizing migrating algorithm (SOMA) is used with ...

— In this paper, the performances of the quasi-Newton BFGS algorithm, the NEWUOA derivative free optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the Differential Evolution (DE) algorithm and Particle Swarm Optimizers (PSO) are compared experimentally on benchmark functions reflecting important challenges encountered in real-world optimization problems. Dependence of the...

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

Differential Evolution (DE) has been shown to be a simple yet efficient evolutionary algorithm for solving optimization problems in continuous search domain. However the performance of the DE algorithm, to a great extent, depends on the selection of control parameters. In this paper, we propose a Replicator Dynamic Inspired DE algorithm (RDIDE), in which replicator dynamic, a deterministic mono...

A new hybrid Optimization Algorithm is proposed to solve Constrained Multi-objective Optimization Problems (CMOPs). The algorithm is named BBO/DE which combines the exploitation ability of Biogeography-based Optimization (BBO) and the exploration ability of Differential Evolution (DE). Meanwhile distance measures and adaptive penalty functions are adopted to handle the constraints so that optim...

Differential Evolution (DE) is a population based search algorithm that comes under the category of evolutionary optimization techniques. It is an improved version of GA, and is exceptionally simple, significantly faster & robust at numerical optimization and is more likely to find a function’s true global optimum. In the present study, DE is used to solve the classical optimization problem of ...

This paper presents an algorithm for solving optimal power flow problem through the application of Differential Evolution (DE). Economic Dispatch is the process of allocating the required load demand between the available generation units such that the cost of operation is minimized. There have been many algorithms proposed for economic dispatch out of which a Differential Evolution (DE) is dis...

A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and ...

Differential Evolution (DE) has been proven to be an efficient and robust algorithm for many real optimization problems. However, it still may converge toward local optimum solutions, need to manually adjust the parameters, and finding the best values for the control parameters is a consuming task. In this paper that proposed a dimension perturb strategy and self-adaptive F value in original DE...