in this study, the stochastic cell formation problem with developing model within queuing theory with stochastic demand, processing time and reliability has been presented. machine as server and part as customer are assumed where servers should service to customers. since, the cell formation problem is np-hard, therefore, deterministic methods need a long time to solve this model. in this study...

In this paper, a genetic algorithm and constriction factor based particle swarm optimization technique are proposed for solving the short term variable head hydrothermal scheduling problem with transmission line losses. The performance efficiency of the proposed techniques is demonstrated on hydrothermal test system comprising of two thermal units and two hydro power plants. the simulation resu...

Induction motor is most frequently used electric machine in various applications due to its well known advantages. The method of vector control help achieve high performance from an induction motor but performance deteriorates due to variation of its parameters. In this paper improved version of Particle Swarm Optimization i.e. Systematic Mutation based Particle Swarm Optimization, SMPSO is use...

The performance of speaker identification is severely degraded in noisy environments. Kim and et al suggested the concept of observation membership for enhancing performances of speaker identification with noisy speech [1]. The method is to weight observation probabilities with observation membership values decided by SNR. In the paper [1], the authors suggested heuristic parameter values for o...

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last decade. They are characterized by a decentralized way of working that mimics the behavior of swarms of social insects, flocks of birds, or schools of fish. The advantage of these approaches over traditional techniques is their robustness and flexibility. These properties make swarm intelligen...

This paper presents a comparative study of Continuous Stirred Tank Reactor concentration control using Particle Swam Optimization and Bacterial Forging Optimization. Continuous stirred tank reactor plays a very important role in process industry. This paper presents the optimal design of PID controller based on Particle Swarm Optimization and Bacterial Forging Optimization. The first step is th...

This study presents a new evolutionary learning algorithm to optimize the parameters of the neural fuzzy classifier (NFC). This new evolutionary learning algorithm is based on a hybrid of bacterial foraging optimization and particle swarm optimization. It is thus called bacterial foraging particle swarm optimization (BFPSO). The proposed BFPSO method performs local search through the chemotacti...

Location problem of multi-distribution center is a kind of NP hard problem. To solve such problems, this paper proposes a chaos adaptive mutation particle swarm optimization algorithm. The algorithm uses the ergodic property of chaos to initialize the particle swarm to enhance the diversity of the population, according to the variance of population fitness to adjust the probability of mutation,...

The classification accuracy of the least squares support vector machine (LSSVM) models strongly depends on proper setting of its parameters. An optimal selection approach of LSSVM parameters is put forward based on multi-swarm cooperative chaos particle swarm optimization (MCCPSO) algorithm. Chaos particle swarm optimization (CPSO) can improve the ability of local search optimization with good ...

This paper mainly discusses the application of the particle swarm optimization in logistics distribution routing problems. Combining with the characteristics of logistics and distribution, it established a mathematical model of the distribution routing problem. Introducing three kinds of optimization strategies in the particle swarm optimization to optimize the particle swarm algorithm, constru...