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The internal rate of return method is currently an important analysis tool for economic feasibility evaluation of engineering project. Against the disadvantages of general methods to calculate internal rate of return, such as big calculation amount, slow speed and low result precision, the calculation of internal rate of return in engineering project was equivalently derived into an optimization problem...
Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared...
Different techniques for the optimization of utility systems have been developed in recent decades. The objective of this paper is to introduce a new mathematical programming model applied to the operational optimization for the utility system. Particle Swarm Optimization (PSO) presented by Kennedy has been described for solving mixed integer linear programming (MILP). It is a simple algorithm that...
Phased-mission system is a kind of broad exist complex system. It has important reference value to research the reliability optimization of this kind of system. For reliability optimization problem of standby phased-mission systems, a method adopts modular fault tree and modular BDD to describe structure of standby system is proposed. The reliability compute method of standby sub-system in phased-mission...
The use of truck-and-trailer systems is an attractive solution to boost the load carrying capacity of land transportation vehicles. However, the steering of such system is problematic due to the lack of sufficient degree-of-freedoms in the available control. The difficulty further increases when obstacles are encountered in the working space. Here, the virtual-robot tracking strategy and force field...
The particle swarm optimization (PSO) algorithm is a swarm intelligence technique, which has exhibited good performance on finding optimal regions of complex search spaces. However, the basic PSO (bPSO) suffers from the premature convergence in multi-modal optimization. This is due to a decease of swarm diversity that leads to the global implosion and stagnation. It is an acceptable hypothesis that...
A new approach is presented to handle constraints optimization using evolutionary algorithms in this paper. First, we present a specific varying fitness function technique, this technique incorporates the problem's constraints into the fitness function in a dynamic way. The resulting varying fitness function facilitates the EA search. On one hand, The new fitness function without any parameters can...
Cloud estimation of distribution particle swarm optimizer combining PSO and cloud model is introduced. In the algorithm's offspring generation scheme, new particles are generated in the cloud estimation of distribution way or in the PSO way. The innovation of the algorithm is production of cloud particles according to the cloud model theory. The cognitive population obtained during optimization is...
This paper presents an application of Differential Evolution (DE) technique to extract small signal model parameters of GaAs metal extended semiconductor field effect transistor (MESFET). DE algorithm is used to minimize the difference between measured and modeled S- parameters to extract the small signal model parameters of the MESFET. The performance of DE algorithm in terms of quality of solution...
Coaxial probe fed rectangular microstrip antenna is a popular type of patch antenna having applications in communication and radar systems. Particle Swarm Optimization (PSO) is a popular optimization algorithm and recently it is being used for design optimization of microstrip patch antennas. In this paper PSO has been used for optimization of resonant frequency of coaxial probe fed rectangular microstrip...
In many applications it is desirable to have the maximum radiation of an array directed normal to the axis of the array. In this paper, the broadside radiation patterns of three-ring Concentric Circular Antenna Arrays (CCAA) with central element feeding are reported. For each optimal synthesis, optimal current excitation weights and optimal radii of the rings are determined having the objective of...
In this paper, particle swarm optimization method is proposed to determine the optimal bidding strategy in competitive electricity market. The market includes Generating companies (Genco's), large consumers who participate in demand side bidding, and small consumers whose demand is present in aggregate form. The effectiveness of the proposed method is tested with IEEE-30 bus system in which six generators...
In the inverse planning optimization of Intensity Modulated Radiation Therapy (IMRT), the Multi-Objective Particle Swarm Algorithm (MOPSA) is applied to optimization the test examples whose objective functions are based on average dose distribution and Dose-Volume Histogram (DVH) respectively. The calculation time, converge speed, numbers of non-inferior solution are compared with two kinds of objective...
The paper proposes a novel neighborhood search operation of particle swarm in the numerical objective space (eg.Rn), and employs the clonal selection strategy which leads the particle swarm to find the optima of the objective space using the neighborhood search operation. So, a novel particle swarm algorithm based on the clonel selection strategy (NPSA/CS) is proposed. In the test experiment, 6 unconstrained...
Optimal operation of reservoir group has been the major issues in optimal operation of water resource systems. On the basis of analysis to the optimal operation of reservoir group, a modified optimizing operation model based on particle swarm optimization (PSO) algorithm was developed for optimal operation of joint water supply from reservoir group. A case study was presented with the application...
The particle swarm optimization (PSO) algorithmis a generally used optimal algorithm, which exhibits good performance on optimization problems in complex search spaces. However, traditional PSO model suffers from a local minima, and lacks of effective mechanism to escape from it. This is harmful to its overall performance. This paper presents an improved PSO model called the stochastic perturbing...
Particle swarm optimization is usually random, which leads to random distribution of search quality and search speed. So the general improved particle swarm optimization is difficult to meet fast optimization needs of some actual engineering. Stocks in the key generation of PSO algorithm generated by uniform design method can make particles in the population maintain a better uniform distribution...
With the development of Web Service, it has become a key issue to select appropriate services from a large number of candidates for creating complex composite services according to users' different QoS levels requirements. However, the existing service selection algorithms have many defects such as high time complexity, non-global optimal solutions, and poor quality solutions. To solve these defects,...
To solve the problems correlated with fuzzy temporal parameter in real manufacture system, based on trapezoidal fuzzy number, a fuzzy single batch-processing machine with non-identical job sizes (NSBM) model for minimized make span and earliness/tardiness penalties which has fuzzy processing time and fuzzy due date is introduced in this paper firstly. After that, aiming at the problems of easily getting...
This paper explores the application of Non-Linear Autoregressive Model with Exogenous Inputs (NARX) system identification of heat exchanger system. Model structure selection was performed using the Binary Particle Swarm Optimization (BPSO) algorithm. The application of BPSO for model structure selection represents each particle's position as binary values, which were used to select a set of regressors...
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