The analysis of flow in water-distribution networks with several pumps by the Content Model may be turned into a non-convex optimization uncertain problem with multiple solutions. Newton-based methods such as GGA are not able to capture a global optimum in these situations. On the other hand, evolutionary methods designed to use the population of individuals may find a global solution even for ...

neural network algorithms have been applied to a variety of areas of engineering and microwave structures. Neural networks are also able to model nonlinear relations between different data sets. Owing to this feature, an introduced neural network model (INN) based on particle swarm optimization (PSO) training algorithm (INN-PSO) is presented for pseudomorphic high electron mobility transistor (...

In this paper, we incorporate pheromone courtship mode of biology to improve particle swarm optimizer. The particle swarm optimization technique has ever since turned out to be a competitor in the field of numerical optimization. A particle swarm optimization consists of a number of individuals refining their knowledge of the given search space. Particle swarm optimizations are inspired by part...

In this paper, hybrid particle swarm optimization (PSO) is proposed for solving the challenging multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problem. The objective of this nonlinear optimization problem is to minimize the total fuel cost of the system and at the same time fulfil the transient stability requirements. The optimal power flow (OPF) with transient...

This paper introduces an effectual technique to solve the DNA sequence assembly problem using a variance of the standard Particle Swarm Optimization (PSO) called the Constriction factor Particle Swarm Optimization (CPSO).The problem of sequence assembly is one of the primary problems in computational molecular biology that requires optimization methodologies to rebuild the original DNA sequence...

Economic load dispatch is a non linear optimization problem which is of great importance in power systems . While analytical methods suffer from slow conversion and curse of dimensionality particle swarm optimization can be an efficient alternative to solve large scale non linear optimization problem.A lot of advancements have been done to modify this algorithm. This paper presents an overview ...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...

This paper presents an efficient and reliable Particle Swarm Optimization (PSO) algorithm for solving Reactive power optimization including voltage deviation in Power System. Voltage deviation is the capability of a power system to maintain up to standard voltages at all buses in the system under standard conditions and under being subjected to a disturbance. Reactive power optimization is a co...

the analysis of flow in water-distribution networks with several pumps by the content model may be turned into a non-convex optimization uncertain problem with multiple solutions. newton-based methods such as gga are not able to capture a global optimum in these situations. on the other hand, evolutionary methods designed to use the population of individuals may find a global solution even for ...