Hybrid biased random sampling for multiple resourse-constrained project scheduling problems

Rainer Kolisch and Andreas Drexl

No 354, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel from Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre

Abstract: In this paper we propose a new heuristic to solve the well-known multiple resource-constrained project scheduling problem. The method is basically a biased random sampling procedure which shows extremely good results by use of the following features: A problem-based selection of the solution space, a sample-size-based guidance of the search, application of a priority rule superior to so-far existing rules, and finally the application of global and local (lower) bounds. Evaluating this new heuristic on a set of widely used benchmark-instances we show that it derives superior results than all other existing polynomially bounded algorithms.

Keywords: Resource-constrained project scheduling; heuristics; biased random sampling (search for similar items in EconPapers)
Date: 1994
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