Grammar-Based Integer Programming Models for Multiactivity Shift Scheduling

It may be very difficult to achieve the optimal shift schedule in call centers which have highly uncertain and peaked demand during short time periods. Overlapping shift systems are usually designed for such cases. This paper studies shift scheduling and rostering problems for inbound call centers where overlapping shift systems are used. An integer programming model that determines which shifts to be opened and how many operators to be assigned to these shifts is proposed for the shift scheduling problem. For the rostering problem both integer programming and constraint programming models are developed to determine assignments of operators to all shifts, weekly days-off, and meal and relief break times of the operators. The proposed models are tested on real data supplied by an outsource call center and optimal results are found in an acceptable computation time. An improvement of 15% in the objective function compared to the current situation is observed with the proposed model for the shift scheduling problem. The computational performances of the proposed integer and constraint programming models for the rostering problem are compared using real data observed at a call center and simulated test instances. In addition, benchmark instances are used to compare our Constraint Programming (CP) approach with the existing models. 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. The originality of this research can be attributed to two contributions: (a) a model for shift scheduling problem and two models for rostering problem are presented in detail and compared using real data and (b) the rostering problem is considered as a task-resource allocation and considerably shorter computation times are obtained by modeling this new problem via CP.

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Equity and Strength in Stochastic Integer Programming Models for the Dynamic Single Aiport Ground-Holding Problem

SSRN Electronic Journal ◽

10.2139/ssrn.3448801 ◽

2018 ◽

Author(s):

Alexander Estes ◽

Michael O. Ball

Keyword(s):

Integer Programming ◽

Programming Models ◽

Stochastic Integer Programming

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Comparisons of three mixed integer programming models for parallel machine scheduling

2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) ◽

10.1109/ieem.2016.7798011 ◽

2016 ◽

Author(s):

Shan-Hao Yu ◽

Yi-Feng Hung

Keyword(s):

Integer Programming ◽

Mixed Integer Programming ◽

Machine Scheduling ◽

Parallel Machine Scheduling ◽

Parallel Machine ◽

Programming Models ◽

Mixed Integer

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Mixed Integer Programming Models on Scheduling Automated Stacking Cranes

International Journal of Business Analytics ◽

10.4018/ijban.2021100102 ◽

2021 ◽

Vol 8 (4) ◽

pp. 11-33

Author(s):

Amir Gharehgozli ◽

Orkideh Gharehgozli ◽

Kunpeng Li

Keyword(s):

Integer Programming ◽

Mixed Integer Programming ◽

Recent Trend ◽

Container Terminals ◽

Programming Models ◽

Mixed Integer ◽

Global Supply Chains ◽

Objective Functions ◽

Operational Constraints ◽

Automated Stacking Cranes

Automated deep-sea container terminals are the main hubs to move millions of containers in today's global supply chains. Terminal operators often decouple the landside and waterside operations by stacking containers in stacks perpendicular to the quay. Traditionally, a single automated stacking cranes (ASC) is deployed at each stack to handle containers. A recent trend is to use new configurations with more than one crane to improve efficiency. A variety of new configurations have been implemented, such as twin, double, and triple ASCs. In this paper, the authors explore and review the mixed integer programming models that have been developed for the stacking operations of these new configurations. They further discuss how these models can be extended to contemplate diverse operational constraints including precedence constraints, interference constraints, and other objective functions.

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