This paper presents a new nature inspired Intelligent Water Drops (IWD) based algorithm for finding peaks in continuous multimodal optimization problems. Initially various conceptual similarities were identified between IWD algorithm and Genetic Algorithm(GA). Simultaneously applying IWD-Continuous Optimization(IWD-CO) algorithm and GA on a function in finding the global optima and found IWDCO ...

the purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. studied refrigeration cycle is compression refrigeration cycle of unit 132 third refineries in south pars that provide chilled water for cooling refinery equipment's. cycle will be performed by ...

Genetic algorithm (GA), as an important intelligence computing tool, is a wide research content in the application domain and the academic circle now. This paper elaborates the improvement of premature convergence in GA used for optimizing multimodal numerical problems. Mutation is the principle operation in Genetic Algorithm (GA) for enhancing the degree of population diversity, but it is prov...

The author proposes an extension of genetic algorithm (GA) for solving fuzzy-valued optimization problems. In the proposed GA, values in the genotypes are not real numbers but fuzzy numbers. Evolutionary processes in GA are extended so that GA can handle genotype instances with fuzzy numbers. The proposed method is applied to evolving neural networks with fuzzy weights and biases. Experimental ...

This paper proposes an algorithm for Public Key Cryptography (PKC) using the hybrid concept of two evolutionary algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) respectively. PSO alone are fast and easy to implement, they follow the procedures of common evolutionary algorithm and posses memory feature which is absent in GA making it more valuable. In GA whole population ...

In previous work we proposed a new evolutionary algorithm , GA , which incorporates features of both the classical search algorithm A and genetic algorithms. In this paper we describe the application of GA to a hard opti-misation problem, route planning in complex terrains for Computer Generated Forces (CGF). We report the performance of the algorithm on a large number of route-planning problem...

A genetic algorithm (GA) is an optimization algorithm that simulates the hereditary phenomenon of natural life. Although GA has been applied to image processing, it has not been studied to apply for matching hand gesture images. In this paper, a method to use GA for the matching process of hand gesture images expressing numbers is proposed. The processing algorithm including GA for hand gesture...

Genetic Algorithms (GA) is well known for searching global maxima and minima[1, 2]. In general, number of search points required by GA for searching global extreme is much lower than the exhausted search. GA has been applied to Block Matching Algorithm (BMA) and demonstrates positively its capability in BMA. The mean square error (MSE) performance of GA based BMA is close to full search (FS). H...

A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The he...