Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked as one of the best search algorithm for solving global optimization problems in several case studies. This paper presents a simple and modified hybridized Differential Evolution algorithm for solving global optimizat...

This research deals with the initial investigations on the concept of a chaos-driven evolutionary algorithm Differential evolution. This paper is aimed at the embedding of simple twodimensional chaotic system, which is Lozi map, in the form of chaos pseudo random number generator for Differential Evolution. The chaotic system of interest is the discrete dissipative system. Repeated simulations ...

A cultural algorithm is proposed in this paper. The main novel feature of this approach is the use of differential evolution as a population space. Differential evolution has been found to be very effective when dealing with real valued optimization problems. The knowledge sources contained in the belief space of the cultural algorithm are specifically designed according to the differential evo...

This paper proposes a novel discrete version of Differential Evolution (NBDE) algorithm to solve combinatorial optimization problems with binary variables. A new binary mutation rule is introduced derived from the table of the basic DE mutation strategy and the value of scaling factor F is 1. The eight different combinations of the three randomly selected individuals using binary encoding are d...

this study proposes a modified version of cultural algorithms (cas) which benefits from rule-based system for influence function. this rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. this is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. this rule ...

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...

This contribution presents the results of an investigation on deterministic spatiotemporal chaos control by means of evolutionary algorithms. Three evolutionary algorithms are used for chaos control: differential evolution, self-organizing migrating algorithm and genetic algorithm. Models of spatiotemporal chaos, so called coupled map lattices, are used. The main aim of this investigation was t...