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An improved particle swarm optimization algorithm (PSO) combined with quantum genetic algorithm is proposed, to solve the problems that the PSO is difficult to converge for benchmark complex problems and it's parameters are hard to define. The new algorithm is used for submersible path planning and simulation on some standard test functions. The results show that the improved is superior to the standard...
Due to the fast convergence, Particle swarm optimization (PSO) has been advocated to be especially suitable for multiobjective optimization. However, there is no information-sharing of with other particles in the population, except that each particle can access the global best. Thus, the premature convergence and lacks of intensification around the local best locations are inevitable during extending...
Recent research on particle swarm optimization (PSO) emphasizes the need to simply this algorithm. This paper is a short study on finding the minimal number of particles in a simplified PSO. We have taken into consideration a social-only variant, Pedersen's simplified PSO, and tested it with four popular optimization benchmark functions in order to discover which is the minimal number of particles...
In this paper, the optimal cross-sectional area of medium voltage feeder will be designed based on particle swarm optimization (PSO) so as to reduce power and energy losses and improve voltage profile in distribution system. To analyze the network status in any step, DC power flow is utilized which is done robustly and with high convergence rate of the system. In the proposed method, medium voltage...
Economic Load Dispatch is one of the most important tasks to be performed in the operation and planning of a power system that decides the generation schedule of generating units with an objective of minimizing the total fuel cost. Normally, the fuel cost of generators can be treated as a quadratic function of real power generation. In fact, valve point loading effect in thermal power plants introduces...
Pixel-level image fusion is widely used in many fields. We proposed a pixel-level image fusion algorithm based on particle swarm optimization with local search, that is, PSO-LS, which improves performance further. PSO-LS integrated the self-improvement mechanisms from memetic algorithms and can avoid local minimum in PSO. Experiments were carried out on two real world images. It is shown that fusion...
In this paper we present a multi-objective optimization approach to optimize a heterogeneous system such as a ship board cooling system. Genetic Algorithm and Evolutionary Programming were used in combination to design the optimization algorithm. The developed multi-objective optimization approach was first implemented and tested on an electrical power system. For this system, voltage stability and...
Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which...
An enhanced particle swarm optimization algorithm (PSO) is presented in this paper to solve the optimal planning of multiple distributed generation sources (DG) in distribution networks. This problem can be divided into two sub-problems: The DG optimal size and location that would minimize the network real power losses. The proposed approach addresses the optimal size and location problems simultaneously...
A computer-aided methodology for designing multiport broadband impedance matching circuits (BIM) to be connected at powerline communication (PLC) networks is presented in order to provide gain equalization and mitigation of the effects of low-impedance loads among transmitter and receivers in a wide frequency range. The design is achieved in successive steps by means of the Vector Fitting method,...
This paper presents a new procedure for identification of multiple cracks in beam. Natural frequency is frequently used as a parameter for detection of cracks in the structures. The process of crack identification in presented procedure is consists of four stages. In first stage, three natural frequencies of a cantilever beam for different locations and depths of cracks were obtained using Finite...
This paper discusses a model predictive control approach to hybrid systems with continuous and discrete inputs. The algorithm, which takes into account a model of a hybrid system, described as Hybrid Automaton. However, to avoid computational complexity and computation time, the nonlinear optimization problem is solved by evolutionary algorithms (EA) such as Genetic Algorithms (GA) and Particle Swarm...
Transmission of high density digital information plays an important role in the present age of communication and information technology. These data are distorted while arriving at the receiver end due to inter symbol interference (ISI) in the channel. The adaptive channel equalizer alleviates this distortion and reconstructs the transmitted data faithfully. In recent years the area of Bacterial Foraging...
In this paper, considering both of access efficiency, order-picking and storage-space cost, a Evolutionary Algorithm Inspired Particle Swarm Optimization (EA-PSO) Algorithm is developed to solve the Warehouse Allocation Problem. Based on the Warehouse Storage Policy, a Class-based storage method is proposed. Moreover, during the procedures goods are ordered by their cube per order index (COI), and...
Economic Load Dispatch is one of the major functions of modern Energy Management System (EMS), which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost. All industrial practice, the fuel cost of generators can be treated as a quadratic function of real power generation. In fact, valve point loading effect in thermal power plants calls...
This paper describes the evaluation of the spreading factor inertia weight Particle Swarm Optimization (PSO) for the fuzzy logic control (FLC) of FES-assisted paraplegic indoor rowing exercise (FES-rowing). The FES-rowing is introduced as a total body exercise for rehabilitation of lower extremities through the application of functional electrical stimulation (FES). FLC is used to control the knee...
This work deals with the optimal control problem which has been proposed to solve using the discrete augmented lagrangian based non-linear programming approach. It is shown that this technique guarantee a satisfactory performance in the face of both optimality by minimizing the energy and maximizing the output. Later on, the optimization has been more effective by using PSO-GA-Based Optimization to...
This paper addresses the problem of identifying the optimal location for power quality monitors.The proposed approach is based on using the integer programming-based model and PSO to solve the optimization problem. Establish a 0-1 sensitivity equation to form the constrains of integer programming by PSCAD/EMTDC.The proposed approach gives the minimum number of power quality monitors and their locations...
This paper proposes a new objective function for solving the optimal management of MicroGrid (MG) problem. This objective function aims to minimize MicroGrid's operating cost as well as the emissions of atmospheric pollutants while constraining it to meet the load demands. Some Objective constraints are presented in this paper for the safety of MG system. Moreover, the particle swarm-based-simulated...
The aim of our study is the optimization after restoring and reconfigure the faulted area in a distribution network after locating and isolating the faulted block. Restoration involves changing the switch status to maximize the supply to loads that are left unsupplied after fault removal. After system optimization using reconfiguration, Field Programmable Gate Array (FPGA) is used in order to control...
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