This paper presents Chemo-tactic PSO-DE (CPSO-DE) optimization algorithm combined with Lagrange Relaxation method (LR) for solving Unit Commitment (UC) problem. The proposed approach employs Chemo-tactic PSO-DE algorithm for optimal settings of Lagrange multipliers. It provides high-quality performance and reaches global solution and is a hybrid heuristic algorithm based on Bacterial Foraging O...

An operational economic model for radio resource allocation in the downlink of a multi-cell WCDMA1 system is developed in this paper, and a particle swarm optimization (PSO) based approach is proposed for its solution. Firstly, we develop an economic model for resource allocation that considers the utility of the provided service, the acceptance probability of the service by the users and the r...

Cloud computing environment can offer dynamic and elastic virtual resources to the end users on demand basis. Task scheduling should satisfy the dynamic requirements of users and also need to utilize the virtual resources efficiently in cloud environment, so that task scheduling in cloud is an NP-Complete problem. In this paper, we present a Hybrid Particle Swarm Optimization (HPSO) based sched...

Social foraging behavior of Escherichia coli bacteria has recently been explored to develop a novel algorithm for distributed optimization and control. The Bacterial Foraging Optimization Algorithm (BFOA), as it is called now, is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real-world optimization problems. Until now, very litt...

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic ...

In this paper a comparison between the single and multi-objective based Optimization techniques including GA, PSO and Hybrid will be presented. The hybrid technique is combined of two attractive evolutionary techniques, Particle Swarm Optimizer (PSO) and Genetic Algorithm (GA) to enhance the search process by improving the diversity, and the convergence toward the preferred solution. This is no...

This paper presents the Wind Energy Conversion System (WECS) combining Permanent Magnet Synchronous Generator (PMSG) with PSO-RNN controller. The proposed hybrid technique uses Particle Swarm Optimization (PSO) algorithm along with Recurrent Neural Network (RNN) which generates the optimal dc reference current. The proposed Maximum Power Point Tracking (MPPT) algorithm finds the maximum operati...

This paper presents a novel heuristic optimization method to solve complex economic load dispatch problem using a hybrid method based on particle swarm optimization (PSO) and gravitational search algorithm (GSA). This algorithm named as hybrid PSOGSA combines the social thinking feature in PSO with the local search capability of GSA. To analyze the performance of the PSOGSA algorithm it has bee...

Yinggan Tang, Leijie Qiao, Xinping Guan Abstract This paper deals with the parameter identification of Wiener model with discontinuous nonlinear. The parameter identification problem is converted to an optimal problem with a suitable objective function. A hybrid optimal method, which integrates the Nelder-Mead simplex search and particle swarm optimization (NM-PSO), is used to optimize the obje...

In this paper a new effective optimization algorithm called hybrid particle swarm optimizer with breeding and subpopulation is presented. This algorithm is essentially, as PSO and GA, a population-based heuristic search technique, now in use for the optimization of electromagnetic structures, modeled on the concepts of natural selection and evolution (GA) but also based on cultural and social r...