The design of reversible systems significantly differs from their conventional counterparts therefore Evolutionary algorithms have been explored in the past for the purpose. In this work, the Enhanced Quantum inspired Evolutionary algorithm is employed for synthesis of various digital and benchmark circuits and its comparative performance analysis with other evolutionary algorithms as well as e...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...

Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Using Metaheuristics models and Evolutionary Algorithms for solving portfolio problem has been considered in recent years.In this study, by using particles swarm optimization and tabu search algorithms we  optimized two-sided risk measures . A standard exact penalty function transforms the considered portfolio selection problem into an equivalent unconstrained minimization problem. And in final...

This report is based on the work I have done for my Master Thesis project. The project as a whole consists of research done in the eld of evolutionary computation, and it is split into two distinct parts. The main theme is adaptive evolutionary algorithms. The rst part covers the research done on solving binary constraint satisfaction problems using adaptive evolutionary algorithms. This involv...

Wildfires cause major damage and losses around the world. Such damages range from human and economical losses to environmental ones. Therefore, having models to predict their behavior can be a key element in the process of firefighting. In this paper, we present a comparative study between two methods we have developed. Both methods use Statistical Analysis, Parallel Evolutionary Algorithms and...