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Volume 44 (2001)
- Issue 4 Pages 301-
- Issue 3 Pages 207-
- Issue 2 Pages 101-
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Volume 44, Issue 1
Displaying 1-12 of 12 articles from this issue
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Article type: Cover
2001 Volume 44 Issue 1 Pages Cover1-
Published: 2001
Released on J-STAGE: June 27, 2017
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Article type: Appendix
2001 Volume 44 Issue 1 Pages App1-
Published: 2001
Released on J-STAGE: June 27, 2017
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Daisuke SatohArticle type: Article
2001 Volume 44 Issue 1 Pages 1-18
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSA discrete Bass model, which is a discrete analog of the Bass model, is proposed. This discrete Bass model is defined as a difference equation that has an exact solution. The difference equation and the solution respectively tend to the differential equation which the Bass model is defined as and the solution when the time interval tends to zero. The discrete Bass model conserves the characteristics of the Bass model because the difference equation has an exact solution. Therefore, the discrete Bass model enables us to forecast the innovation diffusion of products and services without a continuous-time Bass model. The parameter estimations of the discrete Bass model are very simple and precise. The difference equation itself can be used for the ordinary leasts quares procedure. Parameter estimation using the ordinary least squares procedure is equal to that using the nonlinear least squares procedure in the discrete Bass model The ordinary least squares procedures in the discrete Bass model overcome the three shortcomings of the ordinary least squares procedure in the continuous Bass model: the time-interval bias, standard error, and multicollinearity.View full abstractDownload PDF (1389K) -
Liang-Yuh Ouyang, Hung-Chi ChangArticle type: Article
2001 Volume 44 Issue 1 Pages 19-33
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSCost and operation of inventory depends a great deal on what happens to demand when the system is out of stock. In real inventory systems, it is more reasonable to assume that part of the excess demand is backordered and the rest is lost. However, the amount of backorders (or lost sales) often incurs disturbance due to various uncertainties. To incorporate this reality, this article attempts to apply the fuzzy set concepts to deal with the uncertain backorders and lost sales. The purpose of this paper is to modify Moon and Choi's continuous review inventory model with variable lead time and partial backorders by fuzzifying the backorder rate (or equivalently, fuzzifying the lost sales rate). We first consider the case where the lost sales rate is treated as the triangular fuzzy number. Then, through the statistical method for establishing the interval estimation of the lost sales rate, we construct a new fuzzy number, namely statistic-fuzzy number. For each fuzzy case, we investigate a computing schema for the modified continuous review inventory model and develop an algorithm to find the optimal inventory strategy.View full abstractDownload PDF (1040K) -
Keisuke MatsuyamaArticle type: Article
2001 Volume 44 Issue 1 Pages 34-56
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSTwo models are introduced which describe the secular changes of demand in beer and sake. These models, which are given by a set of differential equations, try to describe the demand shift from sake to beer. The competition to be studied in this paper is restricted to this demand shift. The first model is simple. It assumes that the secular trend of beer-demand is expressed by the Logistic Curve. And a certain rate of sake-demand is absorbed into the beer-demand, as the time elapses. The second model, which is rather sophisticated, is obtained by examining the first model. It assumes that the changes in disposable income are explained by the changes of two components, each of which is described by the Logistic Curve. A change of beer-demand is explained by the secular changes of these components. As each equation, which appears in these models, is determined with the given parameters, the method of curve fitting is applied to the time-series data of beer and sake demand. We are to estimate a set of parameters (empirical constants) so that the empirical formulae which explain the actual secular trend of sake and beer demands, may be determined. The results obtained by these models can explain the actual secular trend of beer and sake demand. Moreover by examining the analytical properties of the empirical formulae obtained, the actual change of demands for beer and sake can be described.View full abstractDownload PDF (1611K) -
Miao-Sheng Chen, Chun-Hsiung LanArticle type: Article
2001 Volume 44 Issue 1 Pages 57-66
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSThe Dynamic Production Plan (DPP) Model for reaching an optimal control of the production undergoing the considerations of probabilistic market demand, future obtainable working hour capacity and unreliable machines is proposed in this paper. It can be applied to evaluate the optimal production rate to reduce the risk in the future of uncertainty. It is also suggested that the time interval of production, maintenance cost of an unreliable machine, transaction, penalty, holding costs, sales price and the machine reliability should be taken into considerations. In addition, sensitivity analyses on the key variables of optimal solution are presented. Actually, this study efficiently provides a dynamic tool capable of controlling the production plan (rate) at any time for the production planner having great insight.View full abstractDownload PDF (601K) -
Kazuyuki Sekitani, Iwaro TakahashiArticle type: Article
2001 Volume 44 Issue 1 Pages 67-89
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSSaaty proposes the analyzing methods for AHP using the principal eigenvector of the comparison matrix, and for ANP (analytic network process) using the limiting process method of the powers of the supermatrix. These methods are based on the irreducibility of the evaluation matrices. We develop the unified method solving both AHP and ANP based on Frobenius min-max theorem. Further this method is extended to the solving method of the general (not necessarily irreducible) evaluation matrix, by the graphic decomposition process.View full abstractDownload PDF (1536K) -
Yang Woo ShinArticle type: Article
2001 Volume 44 Issue 1 Pages 90-98
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSWe present an approximation for the stationary distribution πof a countably infinite-state Markov chain with transition probability matrix P=(p_<ij>) of upper Hessenberg form. Our approximation makes use of an associated upper Hessenberg matrix which is spatially homogeneous one P^<(N)> except for a finite number of rows obtained by letting p_<ij>=P_<j-i+1>, i>__-N+1, for some distribution p={p_j} with mean ρ<1, where p_<-j>=0 for j>__-1. We prove that there exists an optimal ρ, say ρ^<*(N)> with which our method provides exact probabilities up to the level N. However, in general to find this optimal ρ^<*(N)> is practically impossible unless one has the exact distribution π. Therefore, we propose a number of approximations to ρ^<*(N)> and prove that a better approximation than that given by finite truncation methods can be obtained in the sense of smaller l_1-distance between exact distribution of its approximation. Numerical experiments are implemented for the M/M/1 retrial queue.View full abstractDownload PDF (583K) -
Article type: Appendix
2001 Volume 44 Issue 1 Pages 99-100
Published: 2001
Released on J-STAGE: June 27, 2017
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Article type: Appendix
2001 Volume 44 Issue 1 Pages App2-
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSDownload PDF (250K) -
Article type: Cover
2001 Volume 44 Issue 1 Pages Cover2-
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSDownload PDF (37K) -
Article type: Cover
2001 Volume 44 Issue 1 Pages Cover3-
Published: 2001
Released on J-STAGE: June 27, 2017
JOURNAL FREE ACCESSDownload PDF (37K)
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