Estimation of the mean waiting time of a customer subject to balking: a simulation study

To a customer, the waiting time for order processing for a product or service is important information for order placement. If the time foreseen for order fulfillment is long, the order might be lost to a competitor. In particular, modern principles of supply chain management highly suggest information sharing between entities in the chain and information technology has enabled customers to conveniently consider the waiting time for a potential balking decision. To help determine the design and operation of a manufacturing or service system in which a customer may balk based on the foreseen waiting time, this paper develops procedures to estimate the average waiting time of an order. Either the procedures allow the maximum waiting time for a balking decision to be random or do not require knowledge of the arrival process of customers before balking if the balking limit is known. For generality of the model, this paper considers general inter-arrival and service time distributions, and uses the simulation and regression approach. J. Jang (&) Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA e-mail: jang@uwm.edu J. Chung Department of Industrial Engineering, Purdue University, West Lafayette, IN 47906, USA e-mail: chung2a@purdue.edu J. Suh Department of Industrial Engineering, Kyungwon University, Sungnam, Korea e-mail: jdsuh@kyungwon.ac.kr J. Rhee Department of Industrial Engineering, Dongguk University, Seoul, Korea e-mail: jtrhee@dongguk.edu 123 Int J Flex Manuf Syst (2007) 18:121–144 DOI 10.1007/s10696-006-9009-x Estimation of the mean waiting time of a customer subject to balking: a simulation study Jaejin Jang Æ Jaewoo Chung Æ Jungdae Suh Æ Jongtae Rhee Published online: 13 February 2007 Springer Science+Business Media, LLC 2007

[1]  David Perry,et al.  Rejection rules in theM/G/1 queue , 1995, Queueing Syst. Theory Appl..

[2]  H. Kaspi,et al.  Inventory systems of perishable commodities , 1983, Advances in Applied Probability.

[3]  David Perry,et al.  The M/G/1 Queue with Finite Workload Capacity , 2001, Queueing Syst. Theory Appl..

[4]  Ronald W. Wolff,et al.  Poisson Arrivals See Time Averages , 1982, Oper. Res..

[5]  M. El-Taha On conditional AstA: A Sample-Path Approach , 1992 .

[6]  S. Brumelle On the relation between customer and time averages in queues , 1971 .

[7]  Ward Whitt,et al.  An Interpolation Approximation for the Mean Workload in a GI/G/1 Queue , 1989, Oper. Res..

[8]  N. R. Srinivasa Raghavan,et al.  Generalized queueing network analysis of integrated supply chains , 2001 .

[9]  Sunggon Kim,et al.  The Virtual Waiting Time of the M/G/1 Queue with Impatient Customers , 2001, Queueing Syst. Theory Appl..

[10]  V. Rykov,et al.  Controlled Queueing Systems , 1995 .

[11]  Toshikazu Kimura A two-moment approximation for the mean waiting time in the GI/G/s queue , 1985 .

[12]  Ward Whitt,et al.  On Arrivals That See Time Averages , 1990, Oper. Res..

[13]  Muhammad El-Taha,et al.  A filtered ASTA property , 1992, Queueing Syst. Theory Appl..

[14]  Jaejin Jang,et al.  A new procedure to estimate waiting time in GI/G/2 system by server observation , 2001, Comput. Oper. Res..

[15]  Jaejin Jang,et al.  Waiting time estimation in a manufacturing system using the number of machine idle periods , 1994 .

[16]  W. Whitt,et al.  Performance of the Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[17]  Sunggon Kim,et al.  Busy Periods of Poisson Arrival Queues with Loss , 2001, Queueing Syst. Theory Appl..

[18]  Toshikazu Kimura APPROXIMATIONS FOR THE WAITING TIME IN THE GI/G/s QUEUE , 1991 .