The Staffing Optimization Problem for the M-Design Multi-Skill Call Center Based on Queuing Model

2019 ◽  
pp. 585-595 ◽  
Author(s):  
Chunyan Li ◽  
Chunxiao Sun ◽  
Jianhua Zhang
Keyword(s):  
Call Center ◽  
Optimization Problem ◽  
Queuing Model

scholarly journals A TIME-VARYING CALL CENTER DESIGN VIA LAGRANGIAN MECHANICS

2009 ◽  
Vol 23 (2) ◽  
pp. 231-259 ◽  
Author(s):  
Robert C. Hampshire ◽  
Otis B. Jennings ◽  
William A. Massey
Keyword(s):  
Call Center ◽  
Fluid Model ◽  
Service Level Agreement ◽  
Service Level ◽  
Lagrangian Mechanics ◽  
Time Varying ◽  
Queuing Model ◽  
Service Network ◽  
Safety Rule ◽  
Loss Systems

We consider a multiserver delay queue with finite additional waiting spaces and time-varying arrival rates, where the customers waiting in the buffer may abandon. These are features that arise naturally from the study of service systems such as call centers. Moreover, we assume rewards for successful service completions and cost rates for service resources. Finally, we consider service-level agreements that constrain both the fractions of callers who abandon and the ones who are blocked.Applying the theory of Lagrangian mechanics to the fluid limit of a related Markovian service network model, we obtain near-profit-optimal staffing and provisioning schedules. The nature of this solution consists of three modes of operation. A key step in deriving this solution is combining the modified offered load approximation for loss systems with our fluid model. We use them to estimate effectively both our service-level agreement metrics and the profit for the original queuing model. Second-order profit improvements are achieved through a modified offered load version of the conventional square root safety rule.

scholarly journals Staffing to Maximize Profit for Call Centers with Impatient and Repeat-Calling Customers

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Jun Gong ◽  
Miao Yu ◽  
Jiafu Tang ◽  
Manru Li
Keyword(s):  
Waiting Time ◽  
Call Center ◽  
Numerical Experiments ◽  
Call Centers ◽  
Arrival Rate ◽  
Customer Behavior ◽  
Queuing Model ◽  
Direct Function ◽  
Many Server Queues

Motivated by call center practice, we study the optimal staffing of many-server queues with impatient and repeat-calling customers. A call center is modeled as an M/M/s+M queue, which is developed to a behavioral queuing model in which customers come and go based on their satisfaction with waiting time. We explicitly take into account customer repeat behavior, which implies that satisfied customers might return and have an impact on the arrival rate. Optimality is defined as the number of agents that maximize revenues net of staffing costs, and we account for the characteristic that revenues are a direct function of staffing. Finally, we use numerical experiments to make certain comparisons with traditional models that do not consider customer repeat behavior. Furthermore, we indicate how managers might allocate staffing optimally with various customer behavior mechanisms.

Exergy and sensibility analysis of each individual effect in a kraft multiple effect evaporator

TAPPI Journal ◽  
2019 ◽  
Vol 18 (10) ◽  
pp. 607-618
Author(s):  
JÉSSICA MOREIRA ◽  
BRUNO LACERDA DE OLIVEIRA CAMPOS ◽  
ESLY FERREIRA DA COSTA JUNIOR ◽  
ANDRÉA OLIVEIRA SOUZA DA COSTA
Keyword(s):  
Optimization Problem ◽  
Real Data ◽  
Kraft Pulping ◽  
Steam Temperature ◽  
Input Flow ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Multiple Effect ◽  
Sensibility Analysis ◽  
Exergetic Analysis

The multiple effect evaporator (MEE) is an energy intensive step in the kraft pulping process. The exergetic analysis can be useful for locating irreversibilities in the process and pointing out which equipment is less efficient, and it could also be the object of optimization studies. In the present work, each evaporator of a real kraft system has been individually described using mass balance and thermodynamics principles (the first and the second laws). Real data from a kraft MEE were collected from a Brazilian plant and were used for the estimation of heat transfer coefficients in a nonlinear optimization problem, as well as for the validation of the model. An exergetic analysis was made for each effect individually, which resulted in effects 1A and 1B being the least efficient, and therefore having the greatest potential for improvement. A sensibility analysis was also performed, showing that steam temperature and liquor input flow rate are sensible parameters.

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