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This paper is concerned with the dynamic pricing problems of a duopoly case in electronic retail markets. Combined with the concept of performance potential, the simulated annealing Q-learning (SA-Q) and the win-or-learn-fast policy hill climbing algorithm (WoLF-PHC) are used to solve the learning problems of multi-agent systems with either average- or discounted-reward criteria, under the case that...
It is a research trend to incorporate neural network with genetic algorithm for solving technical and practical problems. As a single genetic algorithm has slow convergent speed and it is easily falling into local optimum, this paper presents a genetic and simulated annealing hybrid algorithm, which searches the neighborhood using chaos variables. And this paper trains a neural network using the single...
A new classified scheduling method based on the controlled Petri net and GASA was proposed to the job-shop scheduling problem (JSP) with multiple disturbances constrained by machines, workers. Firstly, a Petri net with controller is modeled, it not only has the modeling capability of a traditional Petri net, but also it can depict system characteristics, such as equipment maintenance, different types...
This paper builds an optimal logistics node layout model with considering the land constraints and scale economy of freight based on the analysis of connotation of logistics node layout and does computational analysis to the model by SGA and numerical example simulation in Matlab, the analysis of the example shows that the algorithm can search to the global optimal solution of the problem quickly...
A key challenge of the simulation of deformable soft tissue is to satisfy the conflicting requirements of real-time interactivity and physical realism. The behavior of soft tissue can be described by a mass-spring model provided that correct parameters, such as spring stiffness and viscosity, are used. In practice, such parameters are often determined by trial-and-error based on the visual effects...
A new method of roller bearings fault diagnosis based on least squares support vector machines (LS-SVM) was presented. Feature selection method based on simulated annealing (SA) algorithm was discussed in this paper. LS-SVM classifier was constructed for bearing faults. Compared with the Artificial Neural Network based method, the LS-SVM based method possessed desirable advantages. Experiment shows...
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