A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version
By Kamel Bouleimen, H. Lecocq. European Journal of Operational Research, 2003
582 citations recorded by the source corpus.
Subfields: Industrial and Manufacturing Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/91f9f6c1015fef521f7f793845ce413614485d5e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Industrial and Manufacturing Engineering
- Dirk Briskorn
- Sönke Hartmann
- Mario Vanhoucke
- Vincent Van Peteghem
- Rainer Kolisch
- Jan Weglarz
- Grzegorz Waligóra
- Joanna Józefowska
In Management Science and Operations Research
- Mario Vanhoucke
- Vincent Van Peteghem
- Dirk Briskorn
- Sönke Hartmann
- Rainer Kolisch
- Jan Weglarz
- Grzegorz Waligóra
- Joanna Józefowska
Citations in the corpus
- Experimental investigation of heuristics for resource-constrained project scheduling: An update (2006, methodology): “In fact, on the set J120, random sampling with FBI (which is still a remarkably simple procedure) obtains better results than several more complex approaches including that of Bouleimen and Lecocq [10], one of the two non-dominated methods in our last survey.”
- A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems (2008, methodology): “[16] and the simulated annealing algorithm of Bouleimen and Lecocq [8].”
- A survey of variants and extensions of the resource-constrained project scheduling problem (2010, background): “To capture multiple modes for activities in the notation of Brucker et al. [31], α is set to MPS. Recent papers on this problem class include Alcaraz et al. [6], Bouleimen and Lecocq [25], Hartmann [79], Jarboui et al. [94], Józefowska et al. [97], Özdamar [145] and Pesch [149] while Varma et al. ”
- Project scheduling with finite or infinite number of activity processing modes - A survey (2011, methodology): “simulated annealing (Bouleimen and Lecocq, 2003) and genetic algorithm (Hartmann, 2001) is based on a computational experiment where instances of projects with 10, 12, 14, 16, 18 and 20 activities available in PSPSLIB are used.”
- A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem (2010, methodology): “As the multi-mode is an extension of the single-mode RCPSP, most authors, such as Slowinski et al. (1994), Bouleimen and Lecocq (2003), Hartmann (2001), Jozefowska et al. (2001) and Alcaraz et al. (2003), have used an extension of the standard AL representation.”