Optimal shift scheduling: A branch-and-price approach

Mehrotra, Anuj; Murphy, Kenneth E.; Trick, Michael A.

doi:10.1002/(sici)1520-6750(200004)47:3<185::aid-nav1>3.0.co;2-7

Cited by 39 publications

(28 citation statements)

References 19 publications

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“…The objective is to minimise the number of employees required to perform all daily assignments in the horizon. Several authors have solved personnel scheduling problems using column generation and closely connected branchand-price approaches (Gamache et al, 1999;Mehrotra et al, 2000;Caprara et al, 2003;Beliën and Demeulemeester, 2006;Maenhout and Vanhoucke, 2010).…”

Section: The Personnel Staffing Problemmentioning

confidence: 99%

A heuristic procedure to solve the project staffing problem with discrete time/resource trade-offs and personnel scheduling constraints

Eeckhout

Maenhout

Vanhoucke

2019

Computers & Operations Research

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractWhen scheduling projects under resource constraints, assumptions are typically made with respect to the resource availability and activities are planned each with its own duration and resource requirements. In resource scheduling, important assumptions are made with respect to the staffing requirements. Both problems are typically solved in a sequential manner leading to a suboptimal outcome. We integrate these two interrelated scheduling problems to determine the optimal personnel budget that minimises the overall cost. Integrating these problems increases the scheduling flexibility, which improves the overall performance. In addition, we consider some resource demand flexibility in this research as an activity can be performed in multiple modes. In this paper, we present an iterated local search procedure for the integrated multi-mode project scheduling and personnel staffing problem. Detailed computational experiments are presented to evaluate different decomposition heuristics and comparison is made with alternative optimisation techniques.

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Section: The Personnel Staffing Problemmentioning

confidence: 99%

A heuristic procedure to solve the project staffing problem with discrete time/resource trade-offs and personnel scheduling constraints

Eeckhout

Maenhout

Vanhoucke

2019

Computers & Operations Research

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“…where α a t,o = 1 if shift o assigns activity a in period t, α a t,o = 0 otherwise, and C a t is a cost for doing activity a in period t. In real-life situations, the set Ω is typically very large and the corresponding MIP becomes very hard to solve directly, even via column generation techniques as in Mehrotra et al (2000), Vatri (2001), Bouchard (2004), and Demassey et al (2006).…”

Section: Traditional Models For Cost-driven Schedulingmentioning

confidence: 99%

Retail store scheduling for profit

Chapados

Joliveau

L’Ecuyer

et al. 2014

European Journal of Operational Research

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In spite of its tremendous economic significance, the problem of sales staff schedule optimization for retail stores has received relatively scant attention. Current approaches typically attempt to minimize payroll costs by closely fitting a staffing curve derived from exogenous sales forecasts, oblivious to the ability of additional staff to (sometimes) positively impact sales. In contrast, this paper frames the retail scheduling problem in terms of operating profit maximization, explicitly recognizing the dual role of sales employees as sources of revenues as well as generators of operating costs. We introduce a flexible stochastic model of retail store sales, estimated from storespecific historical data, that can account for the impact of all known sales drivers, including the number of scheduled staff, and provide an accurate sales forecast at a high intra-day resolution. We also present solution techniques based on mixed-integer (MIP) and constraint programming (CP) to efficiently solve the complex mixed integer non-linear scheduling (MINLP) problem with a profit-maximization objective. The proposed approach allows solving full weekly schedules to optimality, or near-optimality with a very small gap. On a case-study with a medium-sized retail chain, this integrated forecasting-scheduling methodology yields significant projected net profit increases on the order of 2-3% compared to baseline schedules.

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“…Possible solution methods include Mehrotra et al (2000), where shift scheduling problems are solved by a branch-and-cut approach, and Eveborn and Ro¨nnqvist (2004), where a branch-and-price approach forms the basis of a practical scheduling system. Branch-and-price has also been applied with success in many cabin crew rostering problems and nurse rostering; see eg Day and Ryan (1997) and Dohn et al (2010).…”

Section: Literature Reviewmentioning

confidence: 99%