A joint chance-constrained programming approach for call center workforce scheduling under uncertain call arrival forecasts
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
Uncertain convex programs: randomized solutions and confidence levels
TL;DR: This paper considers an alternative ‘randomized’ or ‘scenario’ approach for dealing with uncertainty in optimization, based on constraint sampling, and studies the constrained optimization problem resulting by taking into account only a finite set of N constraints, chosen at random among the possible constraint instances of the uncertain problem.
Journal ArticleDOI
A Sample Approximation Approach for Optimization with Probabilistic Constraints
James Luedtke,Shabbir Ahmed +1 more
TL;DR: This work studies approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical distribution obtained from a random sample to obtain a lower bound to the true optimal value.
Journal ArticleDOI
An integer programming approach for linear programs with probabilistic constraints
TL;DR: Computational results indicate that by using the strengthened formulations of PCLP, instances that are considerably larger than have been considered before can be solved to optimality.
Journal ArticleDOI
Concavity and Efficient Points of Discrete Distributions in Probabilistic Programming
TL;DR: The concept of a p-efficient point of a probability distribution is used to derive various equivalent problem formulations and the concept of r-concave discrete probability distributions is introduced.
Journal ArticleDOI
Improving the Sipp Approach for Staffing Service Systems That Have Cyclic Demands
TL;DR: This paper considers Markovian models with sinusoidal arrival rates and proposes two simple modifications of SIPP that will produce reliable staffing levels in models whose parameters span a broad range of practical situations.
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