In this paper, we propose an inventory control method for supply chain planning for single stage production systems under uncertain demand. The planning and scheduling model for uncertain demand situation is developed to represent actual environments for planning and scheduling where variances of future demand are gradually available as the time proceeds. In the proposed method, the amount of shipping for raw materials and safety stock for final products are determined by a stochastic approach by using demand average and variation in feedforward. The quantity of safety stock of inventory for final products is determined by incorporating feedback information from the detailed scheduling results. The effectiveness of the proposed methods is investigated from numerical simulations.
The objective of this paper is to discuss the temperature environment model of automobile's passenger compartments for the analysis of comfortableness and the design of air-conditioning control. To consider the comfortableness, it is necessary to model the distribution of the temperature since almost all the people do not feel the uniform temperature environment to be comfortable. In this paper, we construct the dynamical model of the temperature environment by piecewise modeling technique in which the passenger compartment is divided into plural areas to consider the temperature distribution. And then we verify the performance of the model by comparing the simulation results of the model with experimental results.
In this paper, we propose a new meta-heuristic algorithm for the multidimensional 0-1 knapsack problem (MKP). The proposed method is based on the following four steps. First, a local search is performed in permutation space, where each permutation gives an order of project selection. Second, an initial point (permutation) is determined for the local search by using the information obtained from the solution of a continuously relaxed MKP. Third, a reduction by selection bias (RSB) meta-strategy is applied. Fourth, multi-start points (permutations) are generated by solving the continuously relaxed MKPs with the enumeratively assumed values of some of the variables. To evaluate the proposed method, we used it to solved 60 benchmark problems in the OR-Library and 8 problems in the HCES (Hearin Center for Enterprise Science) resources, and compared the objective values and execution times to those obtained by using existing methods. The results show that the proposed algorithm competes well with the existing ones that are known to be effective.
Compressed digital audio technologies such as MD and MP3, cut down high frequency component data which have less influence on hearing. However, with an increase of compression rate, the increase in sound unclearness is observed. Therefore, a technology to realize high-quality sound is required to respond to the increasing demands for high-quality sound reproduction. In order to meet this challenge, a method is considered, in which the removed high frequency components are reproduced. Focusing attention on the sampled-data control theory to establish an optimum signal processing system using the original sound (CD sound) frequency characteristics, we have applied this theory to high frequency compensation of compressed digital audio signals in the form of “interpolating data points between discrete data to improve signal quality.” As a result, high frequency components of compressed digital audio signals are compensated so that they are close to the frequency spectrum of CDs, which enables sound quality improvement with a remarkably small amount of calculation load. This technology has been implemented on semiconductors which have been commercialized in LSIs for MD players.
This paper deals with trajectory tracking control for non-minimum phase systems. We first consider to characterize output such that it tracks to a given reference signal asymptotically and that the corresponding input is bounded. In particular, we parameterize the error signals between the reference and the achievable output by using Q-parameters in the frequency domain. Since the parameterized set consists of rational functions which are analytic in the closed right half plane, we can solve easily the problem to minimize theL2norm of the error and the analytic solution of the optimal error is obtained. The optimal output is the projection of the reference to the space of achievable outputs. By using the parameterization, the simultaneous optimization of the error and the input deviation from the steady state input can be also solved. The effectiveness of the proposed method is examined by numerical examples.