Integer and combinatorial optimization
Integer and combinatorial optimization
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems
Transportation Science
Selected Topics in Column Generation
Operations Research
Modeling the Regular Constraint with Integer Programming
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Implicit shift scheduling with multiple breaks and work stretch duration restrictions
Journal of Scheduling
A two-stage heuristic for multi-activity and task assignment to work shifts
Computers and Industrial Engineering
Grammar-Based Column Generation for Personalized Multi-Activity Shift Scheduling
INFORMS Journal on Computing
A branch-and-price algorithm for the multi-activity multi-task shift scheduling problem
Journal of Scheduling
| Hi-index | 0.00 |
In some companies such as large retail stores, the employees perform different activities (e.g., cashier or clerk in a specific department) to respond to a customer demand for each activity that varies over the planning horizon and must be fulfilled as soon as possible. For a given time period, this demand translates into an ideal number of employees required for the corresponding activity. During a work shift, an employee can be assigned to several activities that are interruptible at any time and subject to operational constraints (required skills, minimum and maximum assignment durations). Given work shifts already assigned to the employees, the multi-activity assignment problem (MAAP) consists of assigning activities to the shifts such that the activity demands are satisfied as best as possible over the planning horizon. In this paper, we propose three integer programming models for the MAAP and develop various heuristics based on mathematical programming techniques. Computational results obtained on randomly generated MAAP instances show that a heuristic column generation method embedded into a rolling horizon procedure provides the best results in general.