Inventory functions as an adjusting valve to absorb many problems for manufacturers, and it contributes to the activities that maintain daily production. However, it is difficult to accurately grasp the ways in which production acts. In the present study, the problems which arose in inventory at a company were classified as either "phenomenon appearance type problems" or "purpose-setting type problems". Three types of corporate behavior to deal with these two problems were proposed : "holding action", "prior correspondence", and "purpose-setting action". A degree-of-prediction scale was then introduced on the basis of the demonstrative data of the enterprise, and quantification theory was used with the three proposed corporate behaviors to deduce the basic axis of the characteristics that affected inventory.

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To promote efficient science and technology education, we propose Task-given-type Examinations. The processes of Task-given-type Examinations are as follows : 1. The instructor systematically creates a lot of tasks based on the basic regulations of science and technology. 2. The instructor presents the scholars with the tasks. 3. The instructor selects a suitable and appropriate set of tasks from among many tasks. In our Task-Given-Type Examinations, an instructor had to make much effort for working out a number of tasks. The instructor may suffer from that troublesome job. The purpose of this research is to develop a Task-making Supporting System for introducing the Task-given-type Examinations. The system which we developed calculates the subordinate position, base, and relation from the input of a task's data, the knowledge structure data, searches for the solution space by genetic algorithm, and outputs advice on how new tasks should be made. We put our simulation into practice with the supposition that this system would be used for the S-plus education for confirmation of the behavior of this system. Thus we came to the conclusion that we were able to make our system output conducive instructions for educators to create questions which were highly needed to be set and demanding knowledge which was not included in existing questions.

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Generally, it is very important for a software development manager to optimally allocate the financial budget of a development project during the testing phase. Several optimal testing-effort allocation problems for the module testing phase have been discussed to minimize an objective function such as the total testing-effort expenditures, the total residual fault content in the system, the expected total software cost and so on. In this paper, we discuss an optimal effort allocation problem for both the module and integration testing in software development : minimize (residual fault content after the integration testing), subject to (required total testing-effort expenditures during the module and integration testing). We also show an efficient algorithm to solve the problem and provide numerical examples of the derived optimal policies.

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A 2-dimensional rectangular k-within-consecutive-(r,s)-out-of-(m,n):F system is a 2-dimensional version of a consecutive-k-out-of-n:F system. This system consists of m×n components, and fails if and only if a number of components more than or equal to k in any r×s submatrix fail. A 2-dimensional rectangular k-within-consecutive-(r,s)-out-of-(m,n):F system can be treated as a reliability model for TFT Liquid Crystal Display, wireless communication network and so on. An efficient method has been sought for evaluating the system reliability. Though the method is known to be effective for small or medium size systems, the method needs more computation time and more memory capacity, as the system size becomes larger. Therefore, we propose new formulas for upper and lower bounds and approximate value for system reliability, when the system size is large. In this paper, first, we propose new formulas for upper and lower bounds for reliability of the 2-dimensional rectangular k-within-consecutive-(r,s)-out-of-(m,n):F system. We executed some numerical experiments in order to compare our new proposed upper and lower bounds with ones proposed in the preceding studies. According to the results, when the system size is large, our proposed new lower bound is the best lower bound for all the systems. For upper bounds, it was shown that best upper bound depended on the size of matrix r×s, the number of failure components k, and component reliability. When system size is larger than m=50 and n=50, k is much smaller than r×s and component reliability is nearly equal to one, our proposed new upper bound is the best upper bound. Secondly, we propose a limit theorem for the 2-dimensional rectangular k-within-consecutive-(r,s)-out-of-(m,n):F system. This theorem gives us approximate reliabilities of the 2-dimensional rectangular k-within-consecutive-(r,s)-out-of-(m,n):F system, when the system size is large and component reliabilities are nearer to one.

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This paper deals with the three-dimensional container packing problem (3 DCPP) in which a number of items are orthogonally packed onto a rectangular container so that the utilization rate of the container space or the total value of loaded items is maximized. Besides the above objectives, some other practical constraints such as loading stability, the rotation of items about the height direction and the fixed loading (unloading) orders must be considered for real-life 3 DCPP. Firstly, a concept of sub-volumes, similar to sub-areas in the two-dimension problem, and two basic operations between them are proposed. Based upon the generating scheme of the sub-volumes, the packing pattern and its finite enumeration scheme are described. Then, a sub-volume based simulated annealing (SVBSA) algorithm is proposed, which aims at generating flexible and efficient packing patterns and providing a high degree of inherent stability at the same time. Computational experiments on benchmark problems from ORLIBRARY (URL : http://www.ms.ic.ac.uk/info.html) show its efficiency. Although, in theory, the SVBSA algorithm can converge to an optimal packing pattern with probability one after infinite numbers of state transitions, it is not easy to determine an appropriate stopping criterion for each real-life problem. Therefore, an on-line visual representation of the packing pattern is developed in order to trace the search process and stop the algorithm when a satisfactory packing pattern is obtained. Furthermore, for the fixed loading (unloading) order problems the SVBSA algorithm can be simplified into a sub-volume based iterative procedure.

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Recently, investment planning has become very complicated due to rapid changes in the environment external to the company. In particular, short product and technological life cycles result in uncertainty in product mixes, and the evolution of new technologies makes it very difficult for a manager to decide on the size of a facility and the type of technology. This paper describes a model for technology acquisition to determine the technology and the size of investment in the face of uncertainties in product and technological evolution, and products life cycles. Uncertainty in product mixes results from stochastic product stream and overlapping of life cycles, whereas uncertainty in the acceptable choices of technologies results from uncertainty in product mix and technological evolution. This paper introduces a measurement of diversity to represent the complexity of the market environment in order to justify the level of technology. The level of technology is measured by the systems flexibility, where flexibility is the responsiveness of a facility to a diverse environment. A decision model based on a semi-Markov process has been developed. The processes of new product evolution and new technological evolution have been modeled as semi-Markov chains. Based on some hypotheses related to product and technological evolution, this paper derives a possible set of acceptable technologies. Furthermore, several results reflecting the insights of the solution are revealed and discussed. When applied, these insights reduce the state space. Finally the model is implemented on a moderate size problem and the sensitivities of the solution to certain important parameters are discussed.

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A practical solution method for a flow shop scheduling problem to minimize makespan on serial machines under different due date constraints is described. In the flow shop scheduling, when the due date of all jobs is equal, the minimum makespan schedule automatically minimizes the total tardiness of jobs. However, the minimum makespan schedule does not always satisfy the due date constraints when the due date of each job is different. Both the makespan and the tardiness of each job are influenced by the machine idle time and the waiting time of each operation. The idle time and the waiting time depend on the dispersion in processing time as well as the processing sequence. The idle time and waiting time may decrease, if the dispersion in the processing time is made small by dividing each job into some smaller size jobs. Therefore, by dividing jobs, it is possible to generate the desirable schedule which reduces not only the makespan but also the number of tardy jobs and the total tardy time. In this paper, we propose a solution method to generate the smaller makespan schedule satisfying the due date constraints by the application of this approach in the flow shop scheduling problem. This problem may be formulated as a large-scale combinatorial problem to simultaneously decide how to divide each job and in what kind of order to process the divided jobs. An effective solution method does not exist for a large-scale optimal combinatorial problem, so we propose an efficient solution method applying the Genetic Algorithms.

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In recent years, the computer has become indispensable with introduction of O.A. equipment in most offices to enhance work efficiency. Especially in our time, there is a surfeit of information society. Human beings are always exposed to many stimuli. In such a condition we are beginning to feel both physical and emotional stress. Exceeding the limit can cause psychosomatic problems. So it is important to design an efficient work environment which causes the least burden in consideration of human health. Therefore this paper presents a proposal to design factors for a reasonable work environment in Visual Display Terminal (VDT) work in consideration of the influence which work environment factors have on productivity and workload. The method of research used to observe and measure the influence which fragrance and size of office factors have on a worker in VDT work was based on experimental approach. The evaluation index used in this study was obtained from productivity (Quantity, Quality), workload (EEG), a survey of subjective symptoms and eye fatigue. As a result of research, the awaking fragrances of a 20% density and size of office (4m×4m×2m) were found to be important as a reasonable work environment factor in VDT work, and the multiplier effect of them is shown.

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