We have proposed the safety stock model for various demand conditions in the previous papers. The papers gave some solutions for various demand distribution models which change serially and quickly, and proposed the safety stock model whose control is enabled at the fill rate of setting demand sufficiency. This paper is based on the practice of application deployment on the previous study, and we propose the new model which makes the minimum total cost by determining Ordering Point and Order Quantity simultaneously.

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This paper concerns with a sequencing problem to raise the efficiency of line handling in a mixed-model assembly line where products are assembled in the same cycle time. The goal of the sequencing is to attain two objectives simultaneously, i.e., smoothing of work-load and smoothing of part usage. On real mixed-assembly lines, there exist large variations in the assembly times among different product-models. This causes inefficiency such as line stop or increase in idle time. In this paper, we propose a sequencing method to achieve the above two objectives with the help of Relief Man in such situation. For this purpose, the sequencing problem of minimizing both line stop times and idle times is formulated. Since this problem refers to combinational optimization problems, we develop a hierarchical method that applies meta-heuristics like SA (Simulated Annealing) together with NNM (Nearest Neighbor Method). Finally, we examine effectivness of the proposed method through computer simulations.

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We have developed a mill balance control system, which regulates the motor currents and rolling forces of tandem-cold-mill stands while maintaining finish gage accuracy.
The controller is designed using the ILQ design method and constructs a cascade loop outside an automatic-gage-control loop.
The experimental results showed that maximum rolling speeds have increased by 2.4% on average without deterioration of gage accuracy or strip shape.

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Stereo vision is a passive method of obtaining depth information of visible surface by measuring disparity of corresponding points in left and right stereo images. Stereo matching, which belongs to ill-posed problems, is the key issue of stereo vision. In the literature, almost all matching techniques only use gray-scale images. The color information is usually neglected, but undoubtedly it may be of great use in helping robot stereo systems perform better. In this paper, we use two layered self-organization neural network model to simulate the competitive and cooperative interaction of binocular neurons. We propose a special similarity function as initial input to make full use of the color information. In RGB color space, the similarity map is established by taking logical AND calculation of red, green and blue color value similarity. In stereo matching experiment, we first consider color random-dot stereogram for stereo correspondence. Then we take real image experiments by means of different color stereo matching approaches. Experiments results have shown that the quality and convergence speed of the stereo matching can be efficiently improved by using appropriate color matching algorithm comparing with the conventional grey value algorithm.

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Walrasian market is one of the most common economic models for virtual market. In neoclassical economics, it is well-known that the allocation in an equilibrium state of Walrasian market is Pareto optimal. In this paper, we develop several Walrasian virtual markets based on multi-agent paradigm, and validate their Pareto optimality of the allocation by comparing our method with analytic approaches, such as the E-constraint method and the fixed point algorithm. We also discuss the efficiency of our method in terms of caliculation time.

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In this paper, we introduce a new model of acceptor on a three-dimensional pattern, called the time-bounded bottom-up pyramid cellular acceptor with three-dimensional layers whose input tapes are restricted to cubic ones (3-UPC A^C), and investigate a relationship between the accepting powers of 3-UPCA^c's and three-dimesional finite automata whose input tapes are restricted to cubic ones (3-FA^c's). We first show that nondeterministic 3-UPCA^c's are more powerful than nondeterministic 3-FAc's. We next show that O ((diameter) ² × log diameter) time is sufficient for deterministic 3-U PC A^c's to simulate deterministic 3-FAc's, and that O ((diameter) ³) time is sufficient for deterministic 3-UPCA^c's to simulate nondeterministic 3-FA^c's. Finally, we show that Ω ((diameter) ² × log diameter) time is necessary for nondeterministic 3-UPCAc's to simulate alternating 3-FA^c's.

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This paper proposes an enhanced technique of independent component analysis (ICA), which extracts independent components uncorrelated to some external criteria. Fast ICA algorithm is performed after the preprocessing by principal component analysis with external criteria, in which the effects of the external criteria are removed from data sets using regression analysis. The proposed method can also be expanded into local ICA by using hybrid technique of fuzzy clustering and regression analysis. Numerical experiments including knowledge discovery from POS transaction data reveal the characteristic feature of the proposed method.

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