Hybrid biased random sampling for multiple resourse-constrained project scheduling problems - Rainer Kolisch; Andreas Drexl (Universität Kiel, Institut für Betriebswirtschaftslehre; ZBW – Leibniz Information Centre for Economics, 1994)
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: 650; Resource-constrained project scheduling; heuristics; biased random sampling; Produktionssteuerung; Stichprobenerhebung; Theorie