In recent years, DNA-GA algorithm is drawing attention from scholars. The algorithm combines the DNA encoding and Genetic Algorithm, which solves the premature convergence of genetic algorithms, the weak local search capability and binary Hamming cliff problems effectively. How to design a more effective way to improve the performance of DNA-GA algorithm is more worth studying.As is known to al...

The problem of parallel and distributed function optimization is considered. Two coevolutionary algorithms with different degrees of parallelism and different levels of a global coordination are used for this purpose and compared with sequential genetic algorithm (GA). The first coevolutionary algorithm called a loosely coupled genetic algorithm (LCGA) represents a competitive coevolutionary ap...

As one of the evolutionary heuristics methods, genetic algorithms (GAs) have shown a promising ability to solve complex optimization problems. However, existing GAs still have difficulties in finding the global optimum and avoiding premature convergence. To further improve the search efficiency and convergence rate of evolution algorithms, inspired by the mechanism of biological DNA genetic inf...

Multicast (MC) routing algorithms capable of satisfying the quality of services(QoS) requirements of real-time applications will be essential for future high-speed networks. Genetic Algorithms (GA) are stochastic search optimisation methods used in combinatorial optimisation and parameter tuning applications. In this paper, a shared-tree routing protocol based on distributed Genetic Algorithms(...

For traffic prediction forecasting in WIMAX, generally the genetic algorithm were used ,but due to certain limitation of genetic algorithms, problems was created in the traffic prediction .So there is a need to proposed a new approach that is better than Genetic algorithm .this approach need to update the limitation of the Genetics algorithm. There is a need to enhance the prediction capability...

Genetic algorithm (GA) researchers have long desired to describe the key characteristics of GA-hardness. Unfortunately this goal has remained largely unmet. In this paper, we describe a new way for evaluating GA-hardness that is based on the foundations of formal complexity theory. In particular, a GA-reduction is introduced. Using this reduction, we show that a reasonable definition of "GA-har...

Genome rearrangement analysis has attracted a lot of attentions in phylogenetic computation and comparative genomics. Solving the median problems based on various distance definitions has been a focus as it provides the building blocks for maximum parsimony analysis of phylogeny and ancestral genomes. The Median Problem (MP) has been proved to be NP-hard and although there are several exact or ...

This paper addresses a new mixed integer nonlinear and linear mathematical programming economic lot sizing and scheduling problem in distributed permutation flow shop problem with number of identical factories and machines. Different products must be distributed between the factories and then assignment of products to factories and sequencing of the products assigned to each factory has to be d...

The Traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once) where the length of this tour is minimized. Testing every possibility for an N city tour would be N! Math additions. Genetic algorithms (GA) and Memetic algorithms (MA) are a relatively new optimization technique which can be applied to various problems, including those that are ...

Directional overcurrent relays (DOCRs) are widely used to protect power systems. For optimal coordination of DOCRs, several techniques have been proposed to solve this problem. A common way of optimal coordination of DOCRs is using evolutionary algorithms such as genetic algorithm (GA). In this paper, a novel strategy for DOCRs coordination is proposed. In the proposed strategy, a new objective...