Optimal capacity management and planning in services delivery centers

The hotel industry is capital-intensive with high operating leverage in providing accommodations. Examining final costs play very important role in determining of overcapacity and undercapacity. Turkey's experiencing growth in tourism and has remarkable increases in accommodation. This situation possesses great importance for the capital groups investing in this area. How these groups and local tradesman implement a strategy on capacity management is the main question. Single period inventory model is used at the analysis phase and several interests are examined on this topic. Future Room demand is estimated by ARIMA and in estimating cost of undersupply earnings before taxes is used per room night sold. Combining the derived cost ratio with the future room demand and probability distribution estimated from the ARIMA method, the optimal hotel room capacity can be determined. The purpose of the study is to examine hotel room supply and demand for optimal capacity in Turkey.

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Optimal Capacity Management of Substation Transformers Over Long-Run

IEEE Transactions on Power Systems ◽

10.1109/tpwrs.2015.2396576 ◽

2016 ◽

Vol 31 (1) ◽

pp. 632-641 ◽

Cited By ~ 5

Author(s):

Muhammad Humayun ◽

Bruno Jorge Oliveira Sousa ◽

Amir Safdarian ◽

Mubbashir Ali ◽

Merkebu Z. Degefa ◽

...

Keyword(s):

Capacity Management ◽

Optimal Capacity ◽

Long Run

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Stochastic Optimal Capacity Management in Reconfigurable Manufacturing Systems

Journal for Manufacturing Science and Production ◽

10.1515/ijmsp.2004.6.1-2.83 ◽

2004 ◽

Vol 6 (1-2) ◽

pp. 83-88 ◽

Cited By ~ 1

Author(s):

Farshid Maghami Asl, ◽

A. Galip Ulsoy,

Keyword(s):

Manufacturing Systems ◽

Capacity Management ◽

Reconfigurable Manufacturing Systems ◽

Reconfigurable Manufacturing ◽

Optimal Capacity

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Optimal Capacity Management With Stochastic Market Demand and Imperfect Information

Dynamic Systems and Control, Volumes 1 and 2 ◽

10.1115/imece2003-41176 ◽

2003 ◽

Author(s):

Farshid Maghami Asl ◽

A. Galip Ulsoy

Keyword(s):

Imperfect Information ◽

Capacity Management ◽

Management Problem ◽

Market Demand ◽

Economic Stability ◽

New Approach ◽

Optimal Capacity ◽

Markov Decision ◽

Reconfigurable Capacity ◽

Stochastic Market

Over-capacity has been a major problem in the world economy over the past decade. Reconfigurable capacity, and optimal capacity management policies, can contribute to increased economic stability. This research introduces a new approach to optimal capacity management for a firm faced with uncertainties and imperfect information of the market demand. It presents an optimal policy for the capacity management problem in a firm facing stochastic market demand, based on Markov decision theory. To make the approach more realistic, it is assumed that the firm has imperfect information of its stochastic market demand, and can only observe its previous sales. Optimal policies are presented as boundaries representing the optimal capacity expansion and reduction levels.

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Mind the Seat Limit: On Capacity Management in Public Automated Shuttles

Frontiers in Human Dynamics ◽

10.3389/fhumd.2021.689133 ◽

2021 ◽

Vol 3 ◽

Author(s):

Alexander G. Mirnig ◽

Magdalena Gärtner ◽

Vivien Wallner ◽

Elisabeth Füssl ◽

Karin Ausserer ◽

...

Keyword(s):

Public Transport ◽

Human Factor ◽

Public Transit ◽

Capacity Management ◽

Attractive Alternative ◽

Optimal Capacity ◽

Last Mile ◽

User Capacity ◽

Low Degrees ◽

City Centres

With ever growing automation of public transport automated shuttles offer an attractive alternative in areas where traffic regulations limit the deployment of large buses (city centres) or where low degrees of utilization renders the manual vehicles operation non-economical (last mile). The low capacities of shuttles in combination with the human factor (driver or conductor) makes capacity management a greater challenge for the user. Capacity management describes the allocation of available seats in a vehicle, e.g., when buying a ticket. In this paper, we present the results of series of studies where capacity management in automated shuttles has been tested via instruments that are currently available in public transit (audio announcements, in-shuttle displays, booking apps). We found that measures during and after boarding are not sufficient and that capacity management in automated shuttle requires a more detailed planning of pre-boarding stages; when boarding automated shuttles as opposed to non-automated public buses the flexibility is reduced. The paper concludes with discussion and recommendations for an optimal capacity management d.

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