In this paper, we propose a novel Two-stage Particle Swarm Optimization (TSPSO) to solve the problem of virtual enterprise (VE) risk management. A two-level risk management management model is considered. In the top level, the objective of the owner is to maximum the benefit of risk management for the whole VE. In the base level, the partners aim to maximum their benefit of risk management. The...

this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

flexible ac transmission systems (facts) controllers with its ability to directly control the power flow can offer great opportunities in modern power system, allowing better and safer operation of transmission network. in this paper, in order to find type, size and location of facts devices in a power system a dedicated improved particle swarm optimization (dipso) algorithm is developed for de...

This paper proposes a bacterial foraging based approach for portfolio optimization problem. We develop an improved portfolio optimization model by introducing the endogenous and exogenous liquidity risk and the corresponding indexes are designed to measure the endogenous/exogenous liquidity risk, respectively. Bacterial foraging optimization (BFO) is employed to find the optimal set of portfoli...

This paper introduces a Shuffled Frog-Leaping Algorithm based method for the optimization of machining parameters for milling operations. An objective function based on maximum profit in milling operation has been used. The algorithm is compared with others techniques and outperforms the results reached by standard shuffled frogleaping algorithm, differential evolution, particle swarm optimizat...

The current paper describes the application of Particle Swarm Optimization algorithm to the formative e-assessment problem in project management. The proposed approach resolves the issue of personalization, by taking into account, when selecting the item tests in an eassessment, the following elements: the ability level of the user, the targeted difficulty of the test and the learning objective...

The Particle Swarm Optimization is very efficient in intrusion detection in the networks. However, many intrusion detection systems either fail to detect or falsely detect the intrusions. This paper proposes a technique for intrusion detection using Particle Swarm Optimization with Genetic Algorithm based feature selection and using Adaptive Mutation for slow convergence of optimization algorit...

in practical situations, distribution network loads are the mixtures of residential, industrial, and commercial types. this paper presents a hybrid optimization algorithm for the optimal placement of shunt capacitor banks in radial distribution networks in the presence of different voltage-dependent load models. the algorithm is based on the combination of genetic algorithm (ga) and binary part...

Using Metaheuristics models and Evolutionary Algorithms for solving portfolio problem has been considered in recent years.In this study, by using particles swarm optimization and tabu search algorithms we  optimized two-sided risk measures . A standard exact penalty function transforms the considered portfolio selection problem into an equivalent unconstrained minimization problem. And in final...

In practical situations, distribution network loads are the mixtures of residential, industrial, and commercial types. This paper presents a hybrid optimization algorithm for the optimal placement of shunt capacitor banks in radial distribution networks in the presence of different voltage-dependent load models. The algorithm is based on the combination of Genetic Algorithm (GA) and Binary Part...