Metaheuristic optimization algorithms have become popular choice for solving complex and intricate problems which are otherwise difficult to solve by traditional methods. In the present study an attempt is made to review the hybrid optimization techniques in which one main algorithm is a well known metaheuristic; particle swarm optimization or PSO. Hybridization is a method of combining two (or...

In this paper, a hybrid particle swarm optimization algorithm (HPSOM) that uses the mutation process to improve the standard particle swarm optimization (PSO) algorithm is presented. The main idea of the HPSOM is to integrate the PSO with genetic algorithm mutation method. As a result, the proposed algorithm has the automatic balance ability between global and local searching abilities. The val...

QoS multicast routing is a non-linear combinatorial optimization problem that arises in many multimedia applications. Providing QoS support is crucial to guarantee effective transportation of multimedia service in multicast communication. Computing the band-widthdelay constrained least cost multicast routing tree is an NP-complete problem. In this paper, a novel heuristic QoS multicast routing ...

— In this paper, comparative study of two methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is used to solve Economic dispatch problem in power systems. The feasibility of both the methods is demonstrated for a six-generator system and a fifteengenerator system. The results from the experiments show that the PSO method gives a better quality solution to the Economic Dispatch...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...

improving mechanical properties of composites based on strength-to-weight ratio has been gained much attention in various applications. having the most resistant and at the same time the lightest and the most economical structure is believed as an aim in these applications. these three factors are usually opposed to each other. so, applying optimization algorithms for improving mechanical prope...

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by in...

In the context of spectrum surveillance, a new method to recover the code of spread spectrum signal is presented, while the receiver has no knowledge of the transmitter’s spreading sequence. In our previous paper, we used Genetic algorithm (GA), to recover spreading code. Although genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems, but nonethel...

quad rotor is a renowned underactuated unmanned aerial vehicle (uav) with widespread military and civilian applications. despite its simple structure, the vehicle suffers from inherent instability. therefore, control designers always face formidable challenge in stabilization and control goal. in this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nat...

This study investigates the problem of scheduling gantry cranes, which are the main handling equipment in railway container terminals. Since the gantry cranes share two common tracks, some interference constraints are considered for the scheduling problem. The scheduling problem is formulated as an integer programming model. In the view of the high computational complexity, a Particle Swarm Opt...