We use the average hamming distance of a population as a syntactic metric to obtain probabilistic bounds on the time convergence of genetic algorithms. Analysis of a at function provides worst case time complexity for static functions and gives a theoretical basis to the problem of premature convergence. We suggest simple changes that mitigate this problem and help ght deception. Further, emplo...

A planar array antenna with arbitrary geometry synthesis technique based on genetic algorithm is discussed. This approach avoids coding/decoding and directly works with complex numbers to simplify computing programming and to speed up computation. This approach uses two crossover operators that can overcome premature convergence and the dependence of convergence on initial population. Simulatio...

This paper presents an analysis of the relationship of particle velocity and convergence of the particle swarm optimization. Its premature convergence is due to the decrease of particle velocity in search space that leads to a total implosion and ultimately fitness stagnation of the swarm. An improved algorithm which introduces a velocity differential evolution (DE) strategy for the hierarchica...

A main purpose of a multi-objective evolutionary algorithm is to find a good relationship between convergence and diversity of the population. Convergence guides the algorithm to search the optimal solution and diversity tries to avoid a premature stagnation of the search. In multi-objective evolutionary algorithms, diversity has been promoted using different techniques. In this paper, several ...

Error-correcting graph isomorphism has been found useful in numerous pattern recognition applications. This paper presents a genetic-based search approach that adopts genetic algorithms as the searching criteria to solve the problem of error-correcting graph isomorphism. By applying genetic algorithms, some local search strategies are amalgamated to improve convergence speed. Besides, a selecti...

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization ...

This paper presents a GA algorithm for function optimization that combines the features of Simplex crossover and Simulated Aannealing. Hybridization with a local search tool like Simplex directs the GA to more promising search spaces while preventing premature local minima convergence. The use of Simulated Annealing(SA) as a mutation operator further enhances the GA's overall capability. This e...

A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO) algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for m...

The canonical particle swarm optimization (PSO) has its own disadvantages, such as the high speed of convergence which often implies a rapid loss of diversity during the optimization process, which inevitably leads to undesirable premature convergence. In order to overcome the disadvantage of PSO, a perturbed particle swarm algorithm (pPSA) is presented based on the new particle updating strate...

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS....