Aiming at improving search efficiency limitations of canonical real coded genetic algorithm, this paper improves three aspects for the canonical real coded genetic algorithm, that are initial population generating, overall process of algorithm and the mutation operator, then puts forward an improved real coded genetic algorithm. This improved algorithm combines the series operation and parallel...

Genetic Algorithms have been seen as search procedures that can quickly locate high performance regions of vast and complex search spaces, but they are not well suited for fine-tuning solutions, which are very close to optimal ones. However, genetic algorithms may be specifically designed to provide an effective local search as well. In fact, several genetic algorithm models have recently been ...

nowadays network-on-chips is used instead of system-on-chips for better performance. this paper presents a new algorithm to find a shorter path, and shows that genetic algorithm is a potential technique for solving routing problem for mesh topology in on-chip-network.

in this paper, we develop a capacitated location-covering model considering interval values for demand and service parameters. we also consider flexibility on distance standard for covering demand nodes by the servers. we use the satisfaction degree to represent the constraint of service capacity. the proposed model belongs to the class of mixed integer programming models. our model can be redu...

Local Genetic Algorithms are search procedures designed in order to provide an effective local search. Several Genetic Algorithm models have recently been presented with this aim. In this paper we present a new Binary-coded Local Genetic Algorithm based on a Steady-State Genetic Algorithm with a crowding replacement method. We have compared a Multi-Start Local Search based on the Binary-Coded L...

Developing directed mutation methods has been an interesting research topic to improve the performance of genetic algorithms (GAs) for function optimization. This paper introduces a directed mutation (DM) operator for GAs to explore promising areas in the search space. In this DM method, the statistics information regarding the fitness and distribution of individuals over intervals of each dime...

Linkage identification is a technique to recognize decomposable or quasi-decomposable sub-problems. Accurate linkage identification improves GA’s search capability. We introduce a new linkage identification method for Real-Coded GAs called LINC-R (Linkage Identification by Nonlinearity Check for Real-Coded GAs). It tests nonlinearity by random perturbations on each locus in a real value domain....

In real-coded genetic algorithms, some crossover operators do not work well on functions which have their optimum at the corner of the search space. To cope with this problem, we have proposed a boundary extension methods which allows individuals to be located within a limited space beyond the boundary of the search space. In this paper, we give an analysis of the boundary extension methods fro...

It is a well-known fact that genetic algorithms (GAs) are ideal for parallel computers due to their ability to parallely evaluate population members. Most past parallel GA studies have exploited this aspect. Besides resorting to completely different algorithms, such as island models etc., a GA involves a number of other operations which, if parallelized properly, may also end up with a better p...