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Shift scheduling in services when employees have limited availability: An L.P. approach
Author(s) -
Thompson Gary M.
Publication year - 1990
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1016/0272-6963(90)90160-f
Subject(s) - computer science , staffing , schedule , heuristic , scheduling (production processes) , job shop scheduling , flexibility (engineering) , matching (statistics) , mathematical optimization , operations research , mathematics , artificial intelligence , statistics , economics , management , operating system
This paper compares two linear programming (LP) models for shift scheduling in services where homogeneously‐skilled employees are available at limited times. Although both models are based on set covering approaches, one explicitly matches employees to shifts, while the other imposes this matching implicitly. Each model is used in three forms—one with complete, another with very limited meal break placement flexibility, and a third without meal breaks—to provide initial schedules to a completion/ improvement heuristic. The term completion/improvement heuristic is used to describe a construction/ improvement heuristic operating on a starting schedule. On 80 test problems varying widely in scheduling flexibility, employee staffing requirements, and employee availability characteristics, all six LP‐based procedures generated lower cost schedules than a comparison from‐scratch construction/improvement heuristic. This heuristic, which perpetually maintains an explicit matching of employees to shifts, consists of three phases which add, drop, and modify shifts. In terms of schedule cost, schedule generation time, and model size, the procedures based on the implicit model performed better, as a group, than those based on the explicit model. The LP model with complete break placement flexibility and implicitly matching employees to shifts generated schedules costing 6.7% less than those developed by the from‐scratch heuristic.