A VNS algorithm for noisy problems and its application to project portfolio analysis

Authors:
Walter J. Gutjahr;Stefan Katzensteiner;Peter Reiter
Affiliations:
Dept. of Statistics and Decision Support Systems, University of Vienna;Dept. of Statistics and Decision Support Systems, University of Vienna;Dept. of Statistics and Decision Support Systems, University of Vienna
Venue:
SAGA'07 Proceedings of the 4th international conference on Stochastic Algorithms: foundations and applications
Year:
2007

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Abstract

Motivated by an application in project portfolio analysis under uncertainty, we develop an algorithm S-VNS for solving stochastic combinatorial optimization (SCO) problems based on the Variable Neighborhood Search (VNS) metaheuristic, and show its theoretical soundness by a mathematical convergence result. S-VNS is the first general-purpose algorithm for SCO problems using VNS. It combines a classical VNS search strategy with a sampling approach with suitably increasing sample size. After the presentation of the algorithm, the considered application problem in project management, which combines a project portfolio decision on an upper level and project scheduling as well as staff assignment decisions on a lower level, is described. Uncertain work times require a treatment as an SCO problem. First experimental results on the application of S-VNS to this problem are outlined.