blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

Today due to increasing development and importance of petroleum activities andmarine transport as well as due to the mining of seabed, building activities such as construction of docks, platforms and structures as those in coastal areas and oceans has increased significantly. Concrete strength as one of the most important necessary parameters for designing, depends on many factors such as mixtu...

being one of the major research fields in the robotics discipline, the robot motion planning problem deals with finding an obstacle-free start-to-goal path for a robot navigating among workspace obstacles. such a problem is also encountered in path planning of intelligent vehicles and automatic guided vehicles (agvs). traditional (exact) algorithms have failed to solve the problem effectively s...

Research in quantum technology has shown that quantum computers can provide dramatic advantages over classical computers for some problems. The efficiency of quantum computing is considered to become so significant that the study of quantum algorithms has attracted widespread interest. Development of quantum algorithms and circuits is difficult for a human researcher, so automatic induction of ...

this paper investigates the problem of selecting and scheduling a set of projects among available projects. each project consists of several tasks and to perform each one some resource is required. the objective is to maximize total benefit. the paper constructs a mathematical formulation in form of mixed integer linear programming model. three effective metaheuristics in form of the imperialis...

This chapter serves as an introduction to estimation of distribution algorithms. Estimation of distribution algorithms are a new paradigm in evolutionary computation. State-of-the-art EDAs consistently outperform classical genetic algorithms on a broad range of problems. We review the fundamental principles and algorithms that are necessary to understand EDA research. We focus on EDAs for the d...