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In order to solve the problems such as blindfold search, slower convergence, and sometimes unsuccessfully search in the present genetic algorithms used for intelligent test paper generation, this paper introduces an improved genetic algorithm for intelligent test paper generation. This algorithm generates optimized initial chromosome group and controlling crossing and variation recurring to test paper...
Vehicle Routing Problem (VRP) is a NP-complete problem and has important practical value. The Capacitated Vehicle Routing Problem (CVRP) constrained by the capacity of a vehicle is the extension of VRP. In this paper, a two-phase heuristic to address CVRP is proposed. The proposed heuristic has two stages. First, search feasible solution in the global scope using GA. Second, employ local search method...
By analyzing the method of present generating test paper, the article represents a method of generating test paper based on genetic algorithm. A mathematical model for generating test paper is built. By putting forward the intercross operator and mutation operator in consistence with the independent coding, an automatic generation system for test paper is realized.
When GA is used to optimize neural networks, two problems need to be solved. One is the inbreeding and gene coding. Another is the balance between selection pressure and population diversity. One-to-one correspondence between the gene coding and functional equivalence class decreases the coding redundancy through normalizing coding of network. Adaptive crossover and mutation probability is proposed...
According to the problem on calculating the synthetic exponent characterizing the whole performance of radar engine by using the synthetic weighted method, the weights of every parameter are difficult to be determined. To solve this problem, a method of determining the weights of every parameter by adaptive genetic algorithm is presented. The synthetic exponent gained by AGA is more sensitive and...
Positional analysis needs to be made in the Go game, and it is true for professional players or Go program. The present Go program regards the territory scores as a major standard in its positional analysis, which is a flawed approach. In this article, an approach is proposed to calculate the winning probability, and the model parameter is further optimized by genetic algorithm. Through this approach,...
An adaptive Genetic Algorithm (GA) is proposed, which focuses on the automatic adjustments of crossover probability and mutation probability with the changeable environmental parameters. The improved algorithm can overcome some disadvantages of traditional GA, such as, early falling into local optimum, lower convergence speed and large calculation etc. In sequence, the complementary characteristic...
Attribute reduction is one of important problem of rough set theory. In order to get effectively attribute reduction, we presented an algorithm of attribute reduction of rough set based on improved adaptive genetic algorithm (IAGA). IAGA adjusts the crossover probability and mutation probability of each individual according to individual fitness value. The optimization capability and the convergence...
Graph coloring problem is a classical NP-hard combinatorial optimization problem. In this paper, a new bi-objective model for the coloring problem is presented. Based on this new model, a bi-objective genetic algorithm is proposed which employs effective crossover and simple mutation operator as the genetic operators. The global convergence of the proposed algorithm to globally optimal set with probability...
In order to solve the problem of slow convergence speed of adaptive genetic algorithm (AGA) in the early stage of evolution, an improved adaptive genetic algorithm (IAGA) was presented. With the introduction of an indicator evaluating the degree of population diversity, the new algorithm can adaptively adjust the probabilities of crossover. Furthermore, the IAGA was applied to vehicle routing problem...
The problem of logistics partner selection is a key problem in the operational process of fourth party logistics (4PL) model. We propose logistics partner selection index system and use the method of AHP to determine weight coefficient of each index, on the basis of analysis of the influence factors of logistics partner selection under the 4PL model. Whereas the 4PL enterprise usually selects more...
A novel sensor layout method is proposed for bridge health monitoring. The aim of the method is to select sensor locations from a set of possible candidate positions for achieving the best identification of modal frequencies and mode shapes. Sensor layout problem is a combinatorial optimization problem and genetic algorithm is suitable to solve the problem. Commonly, one dimension coding is often...
In this study we discuss a method for evolution of quasigroups with desired properties based on genetic algorithms. Quasigroups are a well-known combinatorial design equivalent to the more familiar Latin squares. One of their most important properties is that all possible elements of certain quasigroup occur with equal probability. The quasigroups are evolved within a framework of a simple hash function...
The aim of test paper composing is to compose an optimization test paper that satisfies the parameters which the user inputs, so the test paper composing problem is a classical multi-objective linear programming problem. After analyzing the mathematical model of the test paper composing problem, this paper converted part of the restricting conditions of test paper composing problem to objective function,...
From the procedure how a locksmith match a key to a lock, a new algorithm called the "key-cutting algorithm" is introduced. There are so many existing algorithms for solving the optimization problem like genetic algorithm, linear programming and the artificial immune algorithm. For any problem these algorithms would apply, so does the key-cutting algorithm. At the same time, some already...
In this paper we describe a method to evolve biologically inspired motion detection systems utilizing artificial neural networks (ANN's). Previously, the evolution of neural networks has focused on feed-forward neural networks or networks with predefined architectures. The purpose of this paper is to present a novel method for evolving neural networks with no predefined architectures to solve various...
Optimization model is build for solving the aircraft departure sequencing problem in this paper first. Then, an improved genetic algorithm (GA) using symbolic coding is proposed, where a type of total probability crossover and big probability mutation are performed. In this way, the evolutionary policy of Particle Swarm Optimization (PSO) is absorbed into the improved GA, which reduces the complexity...
A transmitting beam shaping scheme with limited amplitude weighted values for satellite active phased array antenna is presented to meet lower sidelobe and higher power amplifiers efficiency. The scheme is implemented by a dual coding genetic algorithm (GA) .Phase and amplitude of array weight vectors for shaped beam are encoded by real coding and finite length binary coding, which, maintaining accuracy...
In order to realize the correlating of solar cell's I-V curve, and to obtain the craftwork parameters, we do research on fitting algorithm of solar cell's I-V curve with IRAGA. Firstly, according to the characteristics of solar cell's mathematical model equation, it brings forward correlating with IRAGA. Secondly, we analyze the problems of IRAGA. On the basis of them, we put forward some improved...
Belief measures are widely applied to management of uncertainty in information fusion. In most published applications, the estimations of belief measures that come from empirical rescouses, such as expert systems, are considered to be real belief measures without any validation. We proposed an efficient algorithm that can quickly detect the contradiction between the estimation and requirements of...
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