نتایج جستجو برای: hybrid particle swarm optimization algorithm

تعداد نتایج: 1272720  

2015
K. Geetha P. Thangaraj C. Rasi Priya C. Rajan S. Geetha

This paper presents the performance of Integrated Bacterial Foraging Optimization and Particle Swarm Optimization (IBFO_PSO) technique in MANET routing. The BFO is a bioinspired algorithm, which simulates the foraging behavior of bacteria. It is effectively applied in improving the routing performance in MANET. In results, it is proved that the PSO integrated with BFO reduces routing delay, ene...

Journal: :journal of advances in computer research 2013
behnam barzegar homayun motameni

job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...

Journal: :J. Math. Model. Algorithms 2008
Yannis Marinakis Magdalene Marinaki

This paper introduces a new hybrid algorithmic nature inspired approach based on particle swarm optimization, for solving successfully one of the most popular logistics management problems, the location routing problem (LRP). The proposed algorithm for the solution of the location routing problem, the hybrid particle swarm optimization (HybPSO-LRP), combines a particle swarm optimization (PSO) ...

2015
YANG Jin MA Ma Liang

This paper try to solve the route optimization of stacker in automated storage and retrieval system with the hybrid algorithm which based on the combination of genetic algorithm and particle swarm optimization. First the algorithm generates the initial population by using particle swarm algorithm. And then the population undertakes assorted crossover and mutation in the iterative process by usi...

2013
A. A. El-sawy A. A. Tharwat

A hybrid particle swarm optimization (PSO) for multi-machine time scheduling problem (MTSP) with multicycles is proposed in this paper to choose the best starting time for each machine in each cycle under pre-described time window and a set of precedence machines for each machine; to minimize the total penalty cost. We developed hybrid algorithm by using a combination between PSO and Genetic Al...

M. Shahrouziand , S. Sardarinasab,

For most practical purposes, true topology optimization of a braced frame should be synchronized with its sizing. An integrated layout optimization is formulated here to simultaneously account for both member sizing and bracings’ topology in such a problem. Code-specific seismic design spectrum is applied to unify the earthquake excitation. The problem is solved for minimal structural weight un...

Journal: :Applied Mathematics and Computation 2007
Jing-Ru Zhang Jun Zhang Tat-Ming Lok Michael R. Lyu

The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become very slow. On the contrary, the gradient descending method can achieve faster convergent speed around global optimum, and at the same time, the convergent accuracy can be higher. So in this paper, a hybrid algorithm comb...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

2011
George M. Cavalcanti-Júnior Carmelo J. A. Bastos Filho Fernando Buarque de Lima Neto Rodrigo M. C. S. Castro

Swarm Intelligence algorithms have been extensively applied to solve optimization problems. However, some of them, such as Particle Swarm Optimization, may not present the ability to generate diversity after environmental changes. In this paper we propose a hybrid algorithm to overcome this problem by applying a very interesting feature of the Fish School Search algorithm to the Particle Swarm ...

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