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 ...

Ordered Binary Decision Diagrams are a data structure for representation and manipulation of Boolean functions often applied in VLSI design. The choice of the variable ordering largely influences the size of these structures, size which may vary from polynomial to exponential in the number of variables. A genetic algorithm is applied to find a variable ordering that minimizes the size of ordere...

The Binary Decision Diagram (BDD) is used to represent in symbolic manner a set of states. It’s largely used in the field of formal checking. The variable ordering is a very important step in the BDD optimization process. A good order of variables will reduce considerably the size of a BDD. Unfortunately, the search for the best variables ordering has been showed NP-difficult. In this article, ...

The simple genetic algorithm (SGA) and its convergence analysis are main subjects of the article. A particular SGA is defined on a finite multi-set of individuals (chromosomes) together with mutation and proportional selection operators, each of which with some prescribed probability. The selection operation acts on the basis of the fitness function defined on individuals. Generation of a new p...

A hybrid evolutionary algorithm using scalable encoding method for path planning is proposed in this paper. The scalable representation is based on binary tree structure encoding. To solve the problem of hybrid genetic algorithm and particle swarm optimization, the "dummy node" is added into the binary trees to deal with the different lengths of representations. The experimental results show th...

transmission network expansion planning (tnep) is an important component of power system planning. itdetermines the characteristics and performance of the future electric power network and influences the powersystem operation directly. different methods have been proposed for the solution of the static transmissionnetwork expansion planning (stnep) problem till now. but in all of them, stnep pr...

s: This paper presents a novel approach to improve the performance of genetic algorithms called genetic algorithms with real-coded binary representation (GARB). The proposed algorithm is capable of maintaining the population diversity during the whole run which protects it from premature convergence. This is achieved by using a special encoding scheme with a high redundancy, which is supported ...

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a “data mining-based evolutionary fuzzy expert system” (DEFE...