Browsing by Author "Wang, Tsung-Yin"

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Cost Analysis of a vacation machine repair model
(2011-01-01)
Ke, Jau-Chuan
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Wu, Chia-Huang
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Liou, Cheng-Hwai
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Wang, Tsung-Yin
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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 Society
Estimating Achievable Capacity Index based on Multiple Samples
(2011-01-01)
Wang, Tsung-Yin
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Liou, Cheng-Hwai
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Su, Rung-Hung
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Yang, Dong-Yuh
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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
Optimal control of the N policy M/G/1 queueing system with server breakdowns and general startup times
(2007-10-01)
Wang, Kuo-Hsiung
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Wang, Tsung-Yin
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Pearn, Wen Lea
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工業工程與管理學系
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Department of Industrial Engineering and Management
This paper deals with an N policy M/G/1 queueing system with a single removable and unreliable server whose arrivals form a Poisson process. Service times, repair times, and startup times are assumed to be generally distributed. When the queue length reaches N(N >= 1), the server is immediately turned on but is temporarily unavailable to serve the waiting customers. The server needs a startup time before providing service until there are no customers in the system. We analyze various system performance measures and investigate some designated known expected cost function per unit time to determine the optimal threshold N at a minimum cost. Sensitivity analysis is also studied. (c) 2006 Elsevier Inc. All rights reserved.
Optimization of the T policy M/G/1 queue with server breakdowns and general startup times
(2009-06-01)
Wang, Tsung-Yin
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Wang, Kuo-Hsiung
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Pearn, Wen Lea
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工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper investigates the T policy M/G/1 queue with server breakdowns, and startup times. Customers arrive at the system according to a Poisson process. Service times, repair times, and startup times are assumed to be generally distributed. The server is turned on after a fixed length of time T repeatedly until at least one customer is present in the waiting line. The server needs a startup time before starting the service. We analyze various system performance measures and develop the total expected cost function per unit time in which T is a decision variable. We determine the optimum threshold T* and derive analytical results for sensitivity investigations. The sensitivity analysis is particularly valuable to the system analyst when evaluating future conditions. We also present extensive numerical computation for illustration purpose. (c) 2008 Elsevier B.V. All rights reserved.