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The design objectives of PID controller is to choose the reasonable parameters which can make the system meet the design requirements. Specific to the problem of the controller parameter optimization of flight control system, the classic tuning method of PID controller parameters is cumbersome and need repeating trial. What's more, the controller parameters cannot be guaranteed to be optimal. Therefore,...
We developed an automatic cover design supporting system for non-professional users to create their preferred cover designs in a user-oriented way by using Interactive Genetic Algorithm(IGA). Different from the template design pattern, our system allows an interaction between the algorithm and the Decision Maker(DM). It allows the users to take into account their preferences at each generation of...
This paper introduces a hybrid algorithm combining discrete harmony search (DHS) and iterated local search (ILS) for solving the multi-objective resource allocation problem (RAP). Two objectives are considered simultaneously, i.e. minimization of the overall cost and overall efficiency. The harmony search algorithm is used to conduct the global exploration task, while the iterated local search performs...
There is a huge energy-saving space in sports lighting area, sports lighting designers have taken plenty of measures to save energy, but using the intelligent optimization algorithms to optimize the sports lighting's light environment for energy-saving are rarely studied in domestic. In this paper we take advantage of the evolutionary parallel search abilities of genetic algorithms to find the appropriate...
Multimodal optimization problems are typical those problems where both a global optimum and one or more local optima are included, which can be tackled with by evolutionary algorithms. This paper proposes an improved artificial immune network for multimodal function optimization. In the antibody population, antibodies are allocated to three spaces, i.e., the elitist space, the common space and the...
In this paper, a novel improved multiobjective particle swarm optimization (IMOPSO) is proposed for solving the optimal reactive power dispatch (ORPD) problem with multiple and competing objectives. In order to improve the global search capability and the nondominated solutions diversity, time variant parameters, mutation operator, and dynamic crowding distance are incorporated into the MOPSO algorithm...
NSGA-II(nondominated sorting genetic algorithm II) is a popular multi-objective evolution algorithm (MOEA), which applies binary tournament selection, elitist preserving strategy, nondominated sorting and crowding distance mechanism to obtain a good quality and uniform spread nondominated solution set. In this paper, an improved version of NSGA-II (INSGA-II) is proposed aiming to increase the diversity...
The partner selection and optimization problem is an important area of virtual enterprise (VE). Genetic algorithm (GA) is optimization and parallel strategy simulating biology evolutionary mechanism in nature and a high efficient algorithm solving these types of problems. After analyzing the partner selection problems of virtual enterprise, the improved genetic algorithm (IGA) was presented to solve...
This paper aims at the characteristics of reactive power optimization of the electric power system with the wind farm; proposing a new method for reactive power optimization on the entire power grid which uses the Parallel Immune Particle Swarm Optimization. It uses integer and real number hybrid encoding, improves the efficiency of compiling. And it combines the continuous and discrete particle swarm...
One of the most important features of the PSO algorithm is its fast convergence. This is a positive feature as long as there's no premature convergence. Inspired by the phenomenon of quorum sensing behavior in the bacteria, we incorporate this bio-behavior into PSO and MOPSO to maintain the swarm diversity and promote global exploration when the velocity of each particle in the swarm is rather small...
The product diffusion theory and the optimization theory are introduced to research the quantification of the livable index satisfaction for green coverage of urban and performed the quantitative analysis on the rationality of distribution. Using the statistical curve regression theory and mathematical statistics software SPSS, the utility function of livable index satisfaction for green coverage...
In order to improve convergence speed and precision of optimization in quantum particle swarm optimization (QPSO), an improved quantum particle swarm optimization (IQPSO) algorithm was presented. Chaotic sequences were used to initialize the origin angle position of particle, mutation operation algorithm was used to increase diversity of population and avoid premature convergence. The proposed algorithm...
In order to overcome the disadvantages of premature and local convergence in the traditional particle swarm optimization (PSO), an improved chaotic PSO algorithm based on adaptive inertia weight (AIWCPSO) is proposed. The initial population is generated by using chaotic mapping appropriately, in order to improve both the diversity of population and the periodicity of particles. The value of the new...
In this paper, a fast-sorting method called summation of normalized objectives and diversified selection (SNOV-DS) is embedded in Comprehensive Learning Particle Swarm Optimization (CLPSO) to solve multi-objective problems. Due to this method, the simulation time will be decreased. The convergence to true Pareto front and the spread of solutions can also be improved. The algorithm is tested on a set...
The assessment of high-tech enterprise is of great importance to the government, because a region or even a country's economic development depends largely on the development of high-tech Enterprises in this region or country. According to the problem of Situation Assessment and Prediction of high-tech enterprises in the enterprise cooperation-competition network, the concepts of Brittle Point and...
The correlation degrees among carbon emissions and influencing factors help to make correct judgment and insightful short and long term policies for the low-carbon economy. According to the carbon emissions data provided by American Oak Ridge National Laboratory Carbon Dioxide Information Analysis Center (CDIAC), from which we selected the data of world's top 11carbon emitting countries, a comparative...
At present, the ratio of unemployment was rising slightly in China, and the employment pressure was bigger and bigger than before. To make a scientific explanation for unemployment is the key to solve the focus problem of employment. The study listed seven factors that affect unemployment of labor force by the method of factor analysis and principal component analysis. Seven factors were defined as...
Multiple time lags can occur very naturally in the study of population dynamics. In this paper, we study two forms of the delay logistic equation with two discrete time delays. For both the models, we identify the condition for the first local Hopf bifurcation. For our analysis, we employ a non-dimensional bifurcation parameter. Using Poincaré normal forms and the center manifold theory, we also conduct...
To speed up convergence rate and improve local convergence in genetic algorithm, nonlinear adaptive crossover probability and mutation probability function are designed. They are based on the arctangent function with three parameters of maximal fitness, minimal fitness and average fitness. An improved adaptive genetic algorithm is proposed based on the two designed functions. Simulation results prove...
In this paper, we consider the pest is infected by virus, and the natural enemies have functional response of Beddington-DeAngelis. Making use of Floquet theory, comparison theory and small amplitude perturbations to get the condition of pest-eradication periodic solution locality asymptotical stability and continue existence. The conclusion contributes to control pests.
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