Genetic Algorithms with Local Minimum Escaping Technique

Escaping Hierarchical Traps with Competent Genetic Algorithms

Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search

Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing ’escape’ local optima by accepting nonimproving moves. Another possibility is to dynamically change between representations; a local optimum under one representation may not be a local optimum under another. Shifting is a mechanism which dynamically switches between Gray code repres...

A Hybrid Algorithm using Firefly, Genetic, and Local Search Algorithms

In this paper, a hybrid multi-objective algorithm consisting of features of genetic and firefly algorithms is presented. The algorithm starts with a set of fireflies (particles) that are randomly distributed in the solution space; these particles converge to the optimal solution of the problem during the evolutionary stages. Then, a local search plan is presented and implemented for searching s...

Genetic algorithms for portfolio selection problems with minimum transaction lots

Conventionally, portfolio selection problems are solved with quadratic or linear programming models. However, the solutions obtained by these methods are in real numbers and difficult to implement because each asset usually has its minimum transaction lot. Methods considering minimum transaction lots were developed based on some linear portfolio optimization models. However, no study has ever i...

Genetic algorithms for generating minimum path configurations

Solving a problem on a distributed memory multiprocessor system requires the individual processors to co-operate when necessary, by exchanging messages. These messages are transferred between processors across links which interconnect the processors. If the number of links available at each processor is not restricted then the system may be fully interconnected, having a maximumdistance between...