Pricing and Capacity Sizing of a Service Facility: Customer Abandonment Effects

2019 ◽  
Vol 28 (8) ◽  
pp. 2031-2043 ◽  
Author(s):  
Chihoon Lee ◽  
Amy R. Ward
Keyword(s):  
Service Facility ◽  
Capacity Sizing ◽  
Customer Abandonment

scholarly journals Comparative analysis of models and performance indicators for optimal service facility location

2021 ◽  
Vol 145 ◽  
pp. 102174
Author(s):  
Edoardo Fadda ◽  
Daniele Manerba ◽  
Gianpiero Cabodi ◽  
Paolo Enrico Camurati ◽  
Roberto Tadei
Keyword(s):  
Comparative Analysis ◽  
Facility Location ◽  
Performance Indicators ◽  
Service Facility ◽  
Optimal Service ◽  
And Performance

Evaluation of subway passengers transfer hub congestion based on queuing model and TOPSIS method

2021 ◽  
pp. 1-22
Author(s):  
Xiaokun Wang ◽  
Dong Ni
Keyword(s):  
Queuing Theory ◽  
Evaluation Model ◽  
Flow Characteristics ◽  
Distribution Area ◽  
Flow Density ◽  
Topsis Method ◽  
Queuing Model ◽  
Service Facility ◽  
Passenger Flow ◽  
Topsis Technique

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.

Stability and Chaos in Input Pricing for a Service Facility with Adaptive Customer Response to Congestion

1998 ◽  
Vol 44 (2) ◽  
pp. 246-261 ◽  
Author(s):  
Christopher M. Rump ◽  
Shaler Stidham
Keyword(s):  
Service Facility

Variable capacity sizing and selection of connections in a facility layout

2003 ◽  
Vol 35 (1) ◽  
pp. 49-59 ◽  
Author(s):  
SIMIN HUANG ◽  
RAJAN BATTA ◽  
RAKESH NAGI
Keyword(s):  
Facility Layout ◽  
Capacity Sizing ◽  
Variable Capacity ◽  
Selection Of
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