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Cutting stock is concerned with how to saving material, optimize resources in product designing, manufacturing. It is very complicated and difficult in computing theory, but it has got the extensive application in the actual manufacture. In allusion to the actual characteristics of the genetic algorithm which is applied in the problem of the optimization in rectangular pieces of material, this paper...
In the paper a novel improved genetic algorithm is proposed based on the maximum entropy for thresholding image segmentation. First of all, the encoded mode is made and the maximum entropy function is selected as the key adaptation genetic algorithm, and then the initial group is generated by roulette selection algorithm to the next generation for the best individual, which can improve the global...
Mutation Testing is used as fault-based testing to overcome limitations of other testing approaches but it is recognized as expensive process. In mutation testing, a good test case is one that kills one or more mutants, by producing different mutant output from the original program. Evolutionary algorithms have been proved its suitability for reducing the cost of data generation in different testing...
Time series forecasting is the main method in network flow prediction. RBF neural network is capable of universal approximation, which not only has fast training velocity, but also can solve the local minima problem. Thus, network flow prediction technology based on genetic algorithm and RBF neural network is presented in the paper. And the training parameters are adjusted by genetic algorithm. Network...
An improved and colony algorithm was proposed. Genetic algorithm was utilized to optimize the parameters of ant colony algorithm. The improved algorithm was used to solve the optimization routing of the basic vehicle routing problem. The algorithm possesses some characteristics such as strong total researching ability. The experimental results show that the improved ant colony algorithm possesses...
The paper presents a novel structure for operator of vacuum load-disconnection switch. The fundamental principles and features of this new design are discussed in detail. This is a multiple objective optimization problem, and generic algorithm method is used for the design. It is shown that generic algorithm based optimal design for operator of vacuum load-disconnection switch is feasible and effective,...
The multi-echelon inventory control of weapon equipment repairable spare parts is an important problem for equipment support. In this paper, a genetic algorithm for the multi-inventory problem of repairable spare parts was proposed. In the genetic algorithm, a suitable chromosome representation for multi-inventory problem was presented, and the crossover and mutation operators were investigated. To...
High temperature during system-on-chip (SoC) test often suffers from critical problems such as timing errors, decrease in reliability and even potential damage to chip under test. Thermal-aware test scheduling is an efficient method for ensuring thermal safe during test. The temperature evaluation is a significant research work during thermal-aware test scheduling. A simple and effective temperature...
In this paper with studying of all parameters in grid environment a new scheduling algorithm for independent task is introduced according to Genetic Algorithm. This algorithm can be more efficient and more dependable than similar previous algorithms. The simulated results and reasons for reaching to better makespan and more efficiency in the grid environment. In the grids with high fault with high...
A huge number of routing protocols have been proposed for ad hoc networks to improve the networks' performance. Because of the large number of designs, it's difficult to track all the designs and choose the optimal protocol for an ad hoc network under various scenarios. In addition, it is not clear if any of the original design ideas in the huge number of existing works can be combined to form new...
A huge number of routing protocols have been proposed for ad hoc networks to improve the networks' performance. Because of the large number of designs, it's difficult to track all the designs and choose the optimal protocol for an ad hoc network under various scenarios. Fortunately, a novel architecture named Orchestra has been proposed by Dr. Yaling, Virginia Tech, USA. The architecture decomposed...
In the past decades, the main focus of optimization studies including multi-objective optimization was placed on finding the global optimum or Pareto-optimal solutions. However, in practical engineering, users may not always be interested in finding the so-called global best solutions, particularly when these Pareto-optimal solutions are quite sensitive to the variable perturbations, which cannot...
Container stowage problem with multi-restrictions is a complicated combinatorial optimization problem. It's difficult to obtain an optimal solution. Considering many restrictions in practical applications, an improved genetic algorithm for the optimization of container stowage problem is presented in this paper. Experiment results show that the proposed algorithm is feasible and effective, and can...
Gait recognition is of increasing interest recently. A gait recognition method using the temporal information of leg angles is proposed, based on the fact that changes of leg angles can reflect main trait of a man's moving. First the pendulum model is referred to for extracting leg parts, and least-square method is used for boundary fitting, to obtain the temporal information of angle about thigh...
The cancer classification through gene expression patterns becomes one of the most promising applications of the microarray technology. It is also a significant procedure in bioinformatics. In this study a grid computing based evolutionary mining approach is proposed as discriminant function for gene selection and tumor classification. The proposed approach is based on the grid computing infrastructure...
Baltic Capesize Index is very important for market operators to grip the change of Dry Bulk Shipping Market. This paper is trying to build a forecasting model for BCI (Baltic Capesize Index) based on ANN (Artificial Neural Network) optimized by GA (Genetic Algorithm). The result shows that the model can excellently extract the trend of BCI, and reflect changes in actual value with less error.
Based on FPTA-2, an adaptive binary particle swarm optimization (ABPSO) is proposed to overcome the shortcomings of binary particle swarm optimization (BPSO). Two circuits, an amplifier and an integrator, are evolved to compare ABPSO with genetic algorithm (GA) and Hereboy. Simulation results show ABPSO is a simple and powerful algorithm, well suited for evolvable hardware. It not only has satisfying...
Some characteristics of genetic algorithm just reflect dynamic characteristics of urban spatial growth, thus in order to obtain the quantitative urban growth result, this paper constructs urban spatial growth system based on genetic algorithm and GIS technique. Hereon, the system functions and data are firstly depicted, then system implementation process are further confirmed, including data inputting,...
A solving method with ant colony system for irregular parts nesting was put forward. A method for an irregular part's graph coding and pretreatment was proposed. The proposed method converted the nesting problem into an orthogonal rectangular nesting problem by combining and filling algorithm. By use of remaining rectangle matching and orthogonal accessing algorithm, an automatic nesting system was...
In order to more accurately predict industrial emissions, the paper selected BP and GA-BP neural network to establish the prediction model between the foreign trade and industrial waste discharge. Compared of different forecasting methods and examples of analysis of results, it shows that GA-BP neural network had higher accuracy, tolerant and excellent generalization ability than other model on ecology...
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