Implicit modeling of flexible break assignments in optimal shift scheduling
Management Science
Solving large-scale tour scheduling problems
Management Science
Scheduling workforce and workflow in a high volume factory
Management Science
Optimal shift scheduling with multiple break windows
Management Science
Personnel Tour Scheduling When Starting-Time Restrictions Are Present
Management Science
Staffing and Allocation of Workers in An Administrative Office
Management Science
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Staff scheduling at the United States postal service
Computers and Operations Research
Improving Discrete Model Representations via Symmetry Considerations
Management Science
The State of the Art of Nurse Rostering
Journal of Scheduling
Selecting the appropriate input data set when configuring a permanent workforce
Computers and Industrial Engineering
A two-stage heuristic for multi-activity and task assignment to work shifts
Computers and Industrial Engineering
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The purpose of this paper is to investigate the problem of assigning tasks to workers during their daily shifts. For a homogeneous workforce, a given set of workstation groups, and a corresponding demand for labor, the objective is to develop a disaggregated schedule for each worker that minimizes the weighted sum of transitions between workstation groups. In the formulation of the problem, each day is divided into 48 1/2-hour time periods and a multi-commodity network is constructed in which each worker corresponds to a unique commodity and each node represents a workstation group-time period combination. Lunch breaks and idle time are also included in the model.Initial attempts to solve large instances with a commercial code indicated a need for a more practical approach. This led to the development of a reduced network representation in which idle periods are treated implicitly, and a sequential methodology in which the week is decomposed into 7 daily problems and each solved in turn. To gain more computational efficiency, a tabu search procedure was also developed.All procedures were tested using data obtained from a U.S. Postal Service mail processing and distribution center. Depending on the labor category, anywhere from 3 to 28 workstation groups and up to 311 full-time and part-time workers had to be scheduled together. The results were mixed. While small problems could be solved to near-optimality with the integer programming approaches, tabu search was the best alternative for the very large instances. However, the excessive number of swaps needed to gain marginal improvements, undermined its effectiveness.Combining the two provided a good balance in most cases.