Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/155425
Authors: 
Kolisch, Rainer
Drexl, Andreas
Year of Publication: 
1994
Series/Report no.: 
Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 354
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.
Subjects: 
Resource-constrained project scheduling
heuristics
biased random sampling
Document Type: 
Working Paper

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