Among variety of meta-heuristic population-based search algorithms, particle swarm optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile optimization tool, which incorporates the experience of the whole swarm into the movement of particles. Although the exploitation ability of this algorithm is great, it cannot comprehensively explore the search space and may ...

Formation of effective teams of experts has played a crucial role in successful projects especially in social networks. In this paper, a new particle swarm optimization (PSO) algorithm is proposed for solving a team formation optimization problem by minimizing the communication cost among experts. The proposed algorithm is called by improved particle optimization with new swap operator (IPSONSO...

— 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...

The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage ...

This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and reeursive fdter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic algorithm (GA), that performs a struetored randomized search of an unknown parameter space by manipulating a population of parameter estimates to co...

This paper considers two additional factors of the widely researched vehicle routing problem with time windows VRPTW . The two factors, which are very common characteristics in realworld, are uncertain number of vehicles and simultaneous delivery and pick-up service. Using minimization of the total transport costs as the objective of the extension VRPTW, a mathematic model is constructed. To so...

the multivariate exponentially weighted moving average (mewma) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. the economic design of mewma control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function ...

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...

In recent years, genetic algorithms (GA) and particle swarm optimization (PSO) techniques have attracted considerable attention among various modern heuristic optimization techniques. In this paper PSO is employed for finding stable reduced order models of large-scale linear Interval systems. In this algorithm the numerator and denominator polynomials are determined by minimizing the Integral s...

The construction site layout (CSL) design presents a particularly interesting area of study because of its relatively high level of attention to usability qualities, in addition to common engineering objectives such as cost and performance. However, it is difficult combinatorial optimization problem for engineers. Swarm intelligence (SI) was very popular and widely used in many complex optimiza...