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 new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...

his paper presents the review on image edge detection by using particle swarm optimization and gravitational search algorithm. The paper present the various works done by particle swarm optimization and gravitational search algorithm in the field of digital image processing. By observing the previous works the two optimization algorithms particle swarm optimization algorithm and gravitational s...

This paper assumes each user has more than one queue, derives a new packet dependent proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new schemes of cross-layer packet dependent OFDM scheduling for heterogeneous classes of traffic based on proportional fairness. Scenario 1, scenario 2 and scenario 3 lea...

This paper presented a new particle swarm optimization based on evolutionary game theory (EPSO) for the traveling salesman problem (TSP) to overcome the disadvantages of premature convergence and stagnation phenomenon of traditional particle swarm optimization algorithm (PSO). In addition ,we make a mapping among the three parts discrete particle swarm optimization (DPSO)、 evolutionary game the...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...

In order to optimize the spectrum resource allocation in the orthogonal frequency division multiplexing system and minimize the transmitted power, this paper proposed a modified basic particle swarm optimization algorithm to allocate the subcarriers and bits of the orthogonal frequency division multiplexing system. The algorithm uses the average individual extreme value instead of individual ex...

In this paper, we show a survey of meta-heuristics algorithms based on grouping of animals by social behavior for the Traveling Salesman Problem, and propose a new classification of meta-heuristics algorithms (not based on swarm intelligence theory) based on grouping of animals: swarm algorithms, schools algorithms, flocks algorithms and herds algorithms: a) The swarm algorithms (inspired by th...