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Mario Vanhoucke

Researcher at Katholieke Universiteit Leuven

Publications -  300
Citations -  8718

Mario Vanhoucke is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Schedule (project management) & Project management. The author has an hindex of 46, co-authored 279 publications receiving 7455 citations. Previous affiliations of Mario Vanhoucke include Northwestern Polytechnical University & Ghent University.

Papers
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A comparison of different project duration forecasting methods using earned value metrics

S. Vandevoorde, +2 more
- 01 May 2006 - 
TL;DR: In this paper, the authors compare the classic earned value performance indicators SV and SPI with the newly developed earned schedule performance indicators S( t ) and SPI( t ), and compare the three methods from literature to forecast total project duration.
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A hybrid scatter search/electromagnetism meta-heuristic for project scheduling

Dieter Debels, +4 more
- 01 Mar 2006 - 
TL;DR: This paper combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory to provide near-optimal heuristic solutions for resource-constrained project scheduling.
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A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem

Vincent Van Peteghem, +2 more
- 01 Mar 2010 - 
TL;DR: A bi-population genetic algorithm is applied, which makes use of two separate populations and extend the serial schedule generation scheme by introducing a mode improvement procedure, which reveals that this procedure is amongst the most competitive algorithms.
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RanGen: A Random Network Generator for Activity-on-the-Node Networks

Erik Demeulemeester, +2 more
- 01 Jan 2003 - 
TL;DR: The network generator meets the shortcomings of former network generators since it employs a wide range of different parameters which have been shown to serve as possible predictors of the hardness of different project scheduling problems.
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A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem

Dieter Debels, +1 more
- 01 May 2007 - 
TL;DR: It is illustrated that the GA outperforms all state-of-the-art heuristics and that the DBGA further improves the performance of the GA.