A joint chance-constrained programming approach for call center workforce scheduling under uncertain call arrival forecasts
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TLDR
In this article, a mixed-integer linear programming based solution approach is proposed to solve the shift scheduling problem under uncertain demand forecasts, where forecasting errors are seen as independent normally distributed random variables.About:
This article is published in Computers & Industrial Engineering.The article was published on 2016-06-01 and is currently open access. It has received 16 citations till now. The article focuses on the topics: Stochastic programming & Job shop scheduling.read more
Figures
Table 2: Illustrative example: optimal solutions of problems EDetB and EDetF 
Table 6: Resolution of problem EDetF - instances with σt λt = 1.5 
Table 7: Resolution of problem EDetF - instances with σt λt = 2 
Table 8: Comparison with the sample approximation approach - instances with σt λt = 2 
Figure 2: General risk-cost trade-off analysis 
Table 1: Illustrative example: input data
Citations
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Journal ArticleDOI
A copula-based flexible-stochastic programming method for planning regional energy system under multiple uncertainties: A case study of the urban agglomeration of Beijing and Tianjin
TL;DR: Compared to joint-probabilistic chance-constrained programming (JCP), the CFSP method is more effective for handling multiple random parameters associated with different probability distributions in which their correlations are unknown.
Journal ArticleDOI
Coupling the two-level programming and copula for optimizing energy-water nexus system management – A case study of Henan Province
TL;DR: A copula-based interval two-level programming (CITP) method is applied to planning the energy-water nexus system (EWNS) of Henan Province (China), where various decision-making levels and diverse risk-interaction scenarios are analyzed and results can provide decision supports for the coordinated development of regional-scale EWNS management.
Journal ArticleDOI
An artificial bee colony algorithm for scheduling call centres with weekend-off fairness
Yue Xu,Xiuli Wang +1 more
TL;DR: An enhanced artificial bee colony (EABC) algorithm to solve the workforce scheduling problem in call centres and the experimental results show that the proposed algorithm can achieve (sub-)optimal solutions for large-scale problems.
Journal ArticleDOI
An Integrated Approach for Shift Scheduling and Rostering Problems with Break Times for Inbound Call Centers
TL;DR: The results of the comprehensive computational study indicate that the constraint programming model runs more efficiently than the integer programming model for the rostering problem.
Staffing optimization with chance constraints for emergency call centers
TL;DR: A sample average approximation (SAA) version of this staffing problem with probabilistic constraints in an emergency call center whose solution converges to that of the exact problem when the sample size increases.
References
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Journal ArticleDOI
Optimization of conditional value-at-risk
R. T. Rockafellar,S Uryasev +1 more
TL;DR: In this paper, a new approach to optimize or hedging a portfolio of financial instruments to reduce risk is presented and tested on applications, which focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value at Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well.
Book
Lectures on Stochastic Programming: Modeling and Theory
TL;DR: The authors dedicate this book to Julia, Benjamin, Daniel, Natan and Yael; to Tsonka, Konstatin and Marek; and to the Memory of Feliks, Maria, and Dentcho.
Journal ArticleDOI
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
TL;DR: This work begins with a tutorial on how call centers function and proceed to survey academic research devoted to the management of their operations, which identifies important problems that have not been addressed and identifies promising directions for future research.
Journal ArticleDOI
Convex Approximations of Chance Constrained Programs
TL;DR: A large deviation-type approximation, referred to as “Bernstein approximation,” of the chance constrained problem is built that is convex and efficiently solvable and extended to the case of ambiguous chance constrained problems, where the random perturbations are independent with the collection of distributions known to belong to a given convex compact set.
Journal ArticleDOI
The Modern Call Center: A Multi-Disciplinary Perspective on Operations Management Research
TL;DR: A survey of the recent literature on call center operations management can be found in this article, where the authors identify a handful of broad themes for future investigation while also pointing out several very specific research opportunities.
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