A genetic algorithm for the project assignment problem

Authors:
Paul R. Harper;Valter de Senna;Israel T. Vieira;Arjan K. Shahani
Affiliations:
School of Mathematics, University of Southampton, Southampton S017 1BJ, UK;School of Mathematics, University of Southampton, Southampton S017 1BJ, UK;School of Mathematics, University of Southampton, Southampton S017 1BJ, UK;School of Mathematics, University of Southampton, Southampton S017 1BJ, UK
Venue:
Computers and Operations Research
Year:
2005

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Abstract

In this paper we present a genetic algorithm as an aid for project assignment. The assignment problem illustrated concerns the allocation of projects to students. Students have to choose from a list of possible projects, indicating their preferred choices in advance. Inevitably, some of the more popular projects become 'over-subscribed' and assignment becomes a complex problem. The developed algorithm has compared well to an optimal integer programming approach. One clear advantage of the genetic algorithm is that, by its very nature, we are able to produce a number of feasible project assignments, thus facilitating discussion on the merits of various allocations and supporting multi-objective decision making.