نتایج جستجو برای: improved discrete particle swarm optimization algorithm

تعداد نتایج: 1616317  

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده برق و الکترونیک 1390

there are many approaches for solving variety combinatorial optimization problems (np-compelete) that devided to exact solutions and approximate solutions. exact methods can only be used for very small size instances due to their expontional search space. for real-world problems, we have to employ approximate methods such as evolutionary algorithms (eas) that find a near-optimal solution in a r...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی (نوشیروانی) بابل - دانشکده مهندسی مکانیک 1389

due to the limiting workspace of parallel manipulator and regarding to finding the trajectory planning of singularity free at workspace is difficult, so finding a best solution that can develop a technique to determine the singularity-free zones in the workspace of parallel manipulators is highly important. in this thesis a simple and new technique are presented to determine the maximal singula...

Cellular manufacturing system, an application of group technology, has been considered as an effective method to obtain productivity in a factory. For design of manufacturing cells, several mathematical models and various algorithms have been proposed in literature. In the present research, we propose an improved version of discrete particle swarm optimization (PSO) to solve manufacturing cell ...

L.J. Li, S.K. Zeng,

Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discr...

Journal: :international journal of civil engineering 0
ali kaveh iust omid sabzi iust

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

2010
Huilian FAN

Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal solutions for continuous optimization problems. Updating kinetic equations for particle swarm optimization algorithm are improved to solve traveling salesman problem (TSP) based on problem characteristics and discrete variable. Those strategies which are named heuristic factor, reversion mutant and adaptive no...

2016
Ismail Ibrahim Zuwairie Ibrahim Hamzah Ahmad Zulkifli Md. Yusof

Particle swarm optimization (PSO) has been successfully applied to solve various optimization problems. Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. However, the MSPSO algorithm has to deal w...

Journal: :iranian journal of science and technology transactions of mechanical engineering 2015
w. z. zhao c. y. wang z. q. zhang

differential steering of in-wheel electric vehicle provides the functions of both active steering and power assisted steering with the coupling control of force and displacement transfer characteristic of system. a collaborative optimization model of the differential power-assisted steering system of in-wheel electric vehicle is built, with steering economy as the main system optimization goal,...

2006
Fang Gao Gang Cui Qiang Zhao Hongwei Liu

Partner selection is a critical issue in the research of virtual enterprise. It is usually a combinatorial optimization problem. In this paper, an improved discrete particle swarm algorithm is proposed for the partner selection optimization. At first, an optimization model is presented, which includes the main crucial factors for partner selection, such as running cost, reaction time and failur...

2014
Ming-Fang WANG Jie WANG Xue-Jun ZHAO

The basic thought of particle swarm optimization is introduced firstly, then particle swarm optimization algorithm model is established. The application of the improved particle swarm optimization algorithm to power supply system fault diagnosis is analyzed in accordance with problem of the algorithm, and migration strategy is added to particle swarm optimization algorithm. Finally the paramete...

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