A just-in-time production system was founded by Toyota Motor Corporation. A broad definition of JIT is that only the right amount of necessary goods are supplied in the right place at the right time. Keeping the rate of each part used constant (parts usage leveling goal) is the most important goal in assembly scheduling of mixed-model products in JIT production system. Since the goal-chasing method was proposed, a number of papers have dealt with this problem. The purpose of the JIT production system, however, is not only to reduce inventory levels, but also to reduce inventory costs and increase profits. Until now, this subject has not been discussed in any JIT research. Therefore, in this paper, we propose a new heuristic method for different part compositions and different parts prices in mixed-model assembly scheduling at a single work-station. It is based on a price-based goal-chasing method to decrease variations in the purchasing cost of parts. The main contribution of this paper is that we do not only consider the quantity of parts, but also the purchase price of the parts. A large number of better results shows the effectiveness of the proposed heuristic method through numerical experiments.

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In this paper, we propose a near critical temperature search method which is one of the approximation methods for vehicle routing problems. The near critical temperature search method may effectively solve daily delivery problems by making a few changes to addresses and quantities. The near critical temperature search method is a method similar to the simulated annealing algorithm with a fixed temperature, named critical search temperature, which is a little higher than the critical temperature. The critical temperature is defined as the temperature at which processing time may reach saturation using the near critical temperature search method with a stopping criterion. The stopping criterion is defined to stop the method when the same results of the objective function have been counted up to the appointed number of times in succession through the search. In conventional research, although the simulated annealing algorithm with a fixed temperature has been examined and good results have been found, we have not found any research described how to decide the fixed temperature based on the critical temperature. According to numerical experiments, it turns out that about N^3 searches, where N means the number of customers, can also find the same results as about N^4 searches. Therefore, it has been confirmed that our approximation method is effective for daily delivery problems.

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There are many papers that discuss the sequencing problems of mixed-model assembly lines. It is well known that leveling the work loads at each work station on the assembly line is important. Therefore, the sequencing problems for leveling the work loads have been studied by many researchers and numerous algorithms have been presented. In these papers it is assumed that the operation times of a worker at each work station are deterministic, not stochastic. In fact, the operation times are variable in real production and are determined when the worker finishes his operations. Therefore, we should consider that the operation times of the sequencing problem are stochastic. In this paper, we discuss a sequencing problem for a mixed-model assembly line with stochastic operation times. Firstly, in order to express the operations of each work station on an assembly line with stochastic operation times, we derive a calculation method of the expectations of worker start positions, worker end positions after the operations are completed and utility work. These three expectations cannot be calculated analytically. Then, we propose an approximation calculation method. Though the operation times are continuous random variables, we consider the operation times as discrete random variables and approximately compute the three expectations using transition probabilities. We show that this calculation method is accurate. Using this method, we propose an algorithm, based on simulated annealing, that minimizes the total expectation of utility work. Moreover, we compare a sequencing schedule obtained by our algorithm with a sequencing schedule for minimizing the total utility work through a numerical example, and we demonstrate that these two sequencing schedules are different from each other. Therefore, it is important to determine the objective function of the sequencing problem according to the various related conditions.

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It is significant to obtain optimal solutions or high-quality approximate solutions for multidimensional nonlinear integer programming problems with many decision variables or with large dimensions. It is known that a surrogate constraint method is effective for solving multidimensional problems. The method translates the multidimensional problem into a one-dimensional problem using a surrogate multiplier. When the obtained optimal solution to the surrogate problem is not optimal to the original problem, it is said that there exists a surrogate duality gap between the translated one-dimensional problem and the original multidimensional problem. Nakagawa has recently proposed an improved surrogate constrain (ISC) method that closes the surrogate duality gap and can provide an exact solution to the original problem. The ISC method needs an optimal surrogate multiplier for the surrogate problem. In order to obtain the optimal surrogate multiplier to the problem associated with the original problems with large dimensions, some computational problems should be solved to reduce execution time and working area of memory. Nakagawa et al. have proposed an algorithm that improves Dyer's method for calculating optimal surrogate multipliers. The improved Dyer algorithm proposed reduces the execution time by removing the hyperplanes of the polyhedron that does not influence the calculation of optimal multipliers. In this paper, the effect of the parameters (ratio of Reducing Polyhedron (RP) and period of RP procedure) used in the improved Dyer algorithm is investigated on execution time and the number of executing times by computational experiments. Effective values of the parameters are found for solving the large-scale multidimensional nonlinear integer programming problems in a practical amount of time.

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In the SCM age, the demand and supply gap becomes more risky, and the main concern is directed towards the demand-to-supply management at the aggregate planning stage. This study introduces a game approach to demand-to-supply management by Matsui (2002), and is applied to the e-learning exercise for demand-to-supply management in the AML II project. In the paper, a game-like e-learning method is developed for the collaborative matching of demand (sales) and supply (production) sides (centers). Then, a strategic map is introduced as the collaborative solution of matching. The exercise covers the demand-to-supply planning and management in a make-to-stock enterprise for a period of one year. First, the usual aggregate planning is applied to simple smoothing forecast data with factor α, and the robustness problem to actual sales is discussed. Next, a (N, α)-strategic map with base stock N is introduced, and a collaborative solution is found on the base of profit maximization. Finally, it is shown that the aggregate plan for forecasting base stock is not robust under actual fluctuation in sales, and that the (N, α)-strategic map gives a better robust solution (decision rule). Thus, game-like e-learning with a strategic map would be an effective method.

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With a growing number of Taiwanese tourists visiting Hokkaido, hot-spring resort accommodations in the prefecture have invested in management resources in preparation for prospective customers. It is an important management strategy to identify the customer behavior and interests, and to design accommodation plans accordingly. Consequently, this research involved performing a questionnaire survey in autumn 2001, mainly using the Pair Comparison Method. This survey is aimed at understanding the behavior and needs of Taiwanese tourists and identifying the services they demand in hot-spring resorts. Meanwhile, the Rating Scale Method is a conventional questionnaire approach widely used to examine expectations and importance. However, analysis using answers obtained by this method can cause some problems. For example, the answers in each item cannot be properly prioritized, the response distribution is not symmetrical, etc. To solve these problems, this paper presents a means of measuring of expectation using the Pair Comparison Method, which can directly compare items. Additionally, our analysis employs weights calculated by research findings. Since the weight is based on a ratio scale, it is possible to conduct analyses such as ANOVA. The analysis of variance (ANOVA) and cluster analysis found that Taiwanese visitors place greater importance on tangible factors than intangible factors.

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Forecasting the demand for water supply is very important for pure-water reservoirs. In a previous study, a method of forecasting the demand for water supply on a "per day" basis was proposed based on a regression analysis. However, this method did not consider variations in economic conditions in the service area. In this paper, two new methods for forecasting the demand for water supply on a per day basis, which consider variations in economic conditions for the service area, are proposed. We executed forecasting experiments to compare our proposed methods with the previous proposed method and found out that the forecasted precision of our method is better than that of the previously proposed method. Moreover, regulation factors for forecasting water supply demand per day are tested using a statistical method, because we assume that forecast precision depends on parameters. In this paper, four kinds of parameters are utilized. They are periods of used regression data, methods of correction for regression expression, periods of examination and methods for forecasting water demand per day. As the result of this examination, periods of used regression data, periods of examination and methods for forecasting water demand per day are considered to have a statistical significance.

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We consider facility layout problems where mn machines (facility modules) are assigned mn to cells. These cells are arranged into a rectangular pattern with m rows and n columns. As the objective function, we consider flow costs and adjacent factors between machines. In these facility layout problems, we aim to obtain the machine layout that has the minimum objective value, namely the optimal layout. In obtaining the optimal layout with the existing branch and bound algorithm, we must try to search all layouts. However, in these layouts, there exist obviously many layouts having the same objective function values. For one layout, there exist some layouts obtained by rotation and/or reverse operation. These layouts obviously have the same objective function value. Even if using the existing branch and bound algorithm, we must search the above layouts, and this seems to be inefficient. In this paper, we propose a theorem that states the condition which enumerates only original layouts and automatically removes the layouts that are different due to rotation and/or reverse operation. This condition is called the condition for removing symmetry in this paper. We also propose an efficient algorithm for these facility layout problems using this theorem, which is based on a branch and bound method. We executed some numerical experiments with a personal computer in order to compare our proposed algorithm with the existing algorithms. The results show that our proposed algorithm is useful.

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In traditional reliability tests for assuring the mean time to failure (MTTF) in Weibull distribution with shape and scale parameters, it is assumed that the change of lifetime is concerned with the scale parameter only. Then, Hisada et al. proposed a reliability test procedure for assuring MTTF while considering the influence of both shape and scale parameters. Their reliability test requires complete lifetime data, and the application of a censoring procedure for designing a reliability test for Weibull distribution that considers the influence of both shape and scale parameters has not been considered. In general, since reliability tests require a long testing period, the fixed-number censoring procedure is sometimes applied in order to save testing time. Therefore, in this article we consider the fixed-number censoring procedure in reliability test for assuring MTTF while considering the influence of both shape and scale parameters for Weibull distribution. We also refer to the economical design of the proposed fixed-number censoring test.

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