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Function optimization based on traditional genetic algorithm is easy to fall into local extremum, so that adaptive genetic algorithm is proposed to solve this problem. However, traditional adaptive genetic algorithm has some disadvantages, such as low efficiency and instability. This study presents an improved adaptive genetic algorithm. Specifically, the crossover probability and the mutation probability...
To address the k shortest paths (KSP) problem, an intelligent optimization approach based on Genetic Algorithm (GA) is presented in this paper. A simple and intuitive natural path representation is firstly employed to be the chromosome encoding scheme. Then genetic operators specific to this encoding scheme are defined respectively. Each partial route of two chosen chromosomes is exchanged by a one-point...
A method of milling system operation optimization is proposed in this paper. First, use Support Vector Machine to get the relations between milling unit consumption and its related operation parameters. Second, optimize the model with the help of genetic algorithm and composite algorithm, and then optimal operation parameters of this milling system under different working conditions are got, which...
Maneuver is one of CGF action. For making CGF successfully maneuver in complex battlefield environment, firstly, the model of battlefield environment was established in the way of the rasterization. Second, the CGF model was established according to the maneuver description, and various CGF' behaviors including planning, movement, dodge, pursuit, escape, target track and so on, were considered as...
To address the parameter optimization problem of plate color recognition, two approaches based on IA (immune algorithm) and GA (genetic algorithm) are proposed respectively. Theoretical comparison of IA and GA is first made. Then experimental comparison of the two algorithms is given by using them to perform the parameter optimization task for color recognition of license plates. For plate color recognition...
One crucial task of learning to rank in the field of information retrieval (IR) is to determine an ordering of documents according to their degree of relevance to the user given query. In this paper, a learning method is proposed named AdaGP-Rank by applying boosting techniques to genetic programming. This approach uses genetic programming to evolve ranking functions while a process inspired from...
Wake effect is a key factor leading to the efficiency decrease of the whole wind farm. For different configurations of wind turbines, the accurate prediction of wake effect between wind turbines is vital to the calculation of wind farm cost and benefit. To describe the wake effect better in the wind turbine optimization, a new non-linear wake expansion of the wake model was introduced into the calculation...
To optimize the placement of wind turbines using a genetic algorithm for the fixed size of wind farm, the appropriate computational grids are the basis of the succeeding work. The optimized scheme was tightly restricted by the rationality and accuracy of computational grids. In this paper, based on the consideration of actual wind and wake characteristics of wind turbines, the (a) shape of the grids,...
To solve the problem which is hard to avoid the local optimal solution or slower population diversity when using genetic algorithm to generate the fuzzy rules in a fuzzy system, this paper proposes an automatic rule generation using fuzzy genetic algorithm. This algorithm utilizes the rules population diversity and evolutionary speed to automatically adjust the crossover rate and mutation rate based...
The successful application of fuzzy control largely depends on some subjectively decided parameters, such as fuzzy membership functions. In this paper, genetic learning and turning based on real-coded genetic algorithm is proposed to automatically design and optimize the fuzzy membership function's parameters. An advantage framework, which can achieve a trade-off between execution time and optimized...
In order to improve the real-time performance of the switched Ethernet, genetic algorithm is used to optimize the subnet partition. Firstly, the existing methods are analyzed. Secondly, a linked list encoding and new operators for this special encoding are designed. Then, based on the network calculus, the calculating expression of the maximum network delay is proposed. Lastly, an experiment on ring...
The ant colony algorithm (ACA) has been successfully applied to several combinatorial optimization problems, but it has some shortcomings such as its slow computing speed, and it is easy to fall into local optimal. So a hybrid ant colony algorithm is proposed to optimize the ACA parameters. Firstly, the basic feasible solutions are solved by ACA, and then the quadratic optimal results are gotten by...
A genetic algorithm (GA) based approach to solve a fuzzy multi-objective nonlinear programming (FMNP) problem is presented and applied to water resources allocation. A FMNP model of regional water allocation is established originally. The objective functions of the model include three conflicting goals which are economic profits, environment goal and society goal. By turning the FMNP to an optimal...
DNA encoding problem, which has been proved to be an NP hard problem, is a key problem for DNA computing, and usually solved by optimization algorithms. A new efficient genetic algorithm based on cultural algorithm for the design of DNA codewords is presented in this paper. In this hybrid optimization method, to abstract and manage the information efficiently, the conventional genetic algorithm is...
Evolutionary encryption is a new focus in recent research work. The new method of design encryption is to combine evolution algorithm with encryption designing. Boolean function is very import in encryption. The traditional method of optimizing Boolean function is algebra method which is slow and difficult. We propose an optimization algorithm for the Boolean function based on GEP. Comparing to the...
This paper presents active disturbance rejection control system for toggle-motor coupling servomechanism system. Genetic algorithm and mixed H2/Hinfin norm index are utilized to optimize the system parameters; Monte-Carlo method is applied to evaluate the robustness of the control system. Simulation results show that under the condition of external disturbance, parameters perturbation and coupling,...
The Analog circuits are very important in many high-speed applications such as communications. Since the size of analog circuit is becoming larger and more complex, the design is becoming more and more difficult. This paper proposes a new circuit representation method based on a two-layer evolutionary scheme with genetic programming (TLGP), which uses a divide-and-conquer approach to evolve the analog...
Evolutionary hardware (EHW) is a new focus in recent research work. The new method of design hardware is combined evolution algorithm with programmable logic device. Optimization digital circuit is a main domain of EHW. The algebra way and Karnaugh map way are the traditionary methods, but they will meet trouble with the large scale ones to get optimization structure of circuit. This paper proposes...
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In this paper, we propose a new GP framework, namely, instruction-matrix (IM)-based GP (IMGP), to handle their interactions. IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from...
Controller Area Network (CAN), a typical event- triggered protocol, has been widely used in constructing distributed real time network. A common opinion is that the arbitration mechanism of CAN might introduce jitters, which is highly undesirable in time and safety critical applications. Time-triggered protocols address exactly the problem. Time- triggered protocols, such as Flexray, Time-Triggered...
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