A genetic algorithm approach for a constrained employee scheduling problem as applied to employees at mall type shops

Authors:
Adrian Brezulianu;Monica Fira;Lucian Fira
Affiliations:
Technical University of Iasi, Iasi, Romania;Romanian Academy, Iasi, Romania;Technical University of Iasi, Iasi, Romania
Venue:
Proceedings of the 2009 International Conference on Hybrid Information Technology
Year:
2009

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Abstract

In this application of artificial intelligence to a real-world problem, the constrained scheduling of employee resourcing for a mall type shop is solved by means of a genetic algorithm. Chromosomes encode a one-week schedule and a constraint matrix handles all requirements for the population. The genetic operators are purposely designed to preserve all constraints and the objective function assures an imposed coverage, this is for people on both sections of the mall. The results demonstrate that the genetic algorithm approach can provide acceptable solutions to this type of employee scheduling problem with constrains.