Browsing by Author "Liou, Cheng-Hwai"
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Item type:Item, Cost Analysis of a vacation machine repair model(2011-01-01) ;Ke, Jau-Chuan ;Wu, Chia-Huang ;Liou, Cheng-Hwai ;Wang, Tsung-Yin工業工程與管理學系This paper investigates a machine repair problem with homogeneous machines and standbys available, in which multiple technicians are responsible for supervising these machines and operate a (R, V, K) synchronous vacation policy. With such a policy, if any V idle technicians exist in the system, these V (V < R) technicians would take a synchronous vacation. Upon returning from vacation, they would take another vacation if there is no broken machine waiting in the queue. This pattern continues until at least one failed machine arrives. It is assumed that the number of teams/groups on vacation is less than or equal to K (0 <= KV < R). The matrix analytical method is employed to obtain a steady-state probability and the closed-form expression of the system performance measures. Efficient approaches are performed to deal with the optimization problem of the discrete / continuous variables while maintaining the system availability at a specified acceptable level. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Asia Pacific Business Innovation and Technology Management SocietyItem type:Item, Estimating Achievable Capacity Index based on Multiple Samples(2011-01-01) ;Wang, Tsung-Yin ;Liou, Cheng-Hwai ;Su, Rung-Hung ;Yang, Dong-Yuh工業工程與管理學系This paper investigates the profitability which measures for the newsboy-type product and develops a new index "Achievable Capacity Index", denoted by I-A. It can accurately measure the profitability of newsboy-type product with normally distributed demand. Furthermore, the interrelationship between profitability and I-A is also performed. An unbiased and effective estimator is derived to estimate I-A. Practically, market information regarding demand is obtained from multiple samples rather than single sample. Then we estimate I-A based on multiple samples. Finally, a numerical result is presented to show the probability density function of the unbiased estimator of (I) over cap (A) under different groups and sample sizes. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Asia Pacific Business Innovation and Technology Management Society