A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem
AbstractWe consider the multi-mode resource-constrained project scheduling problem (MRCPSP), where a task has different execution modes characterized by different resource requirements. Due to the nonrenewable resources and the multiple modes, this problem is NP-hard; therefore, we implement an evolutionary algorithm looking for a feasible solution minimizing the makespan. In this paper, we propose and investigate two new ideas. On the one hand, we transform the problem of single objective MRCPSP to bi-objective one to cope with the potential violation of nonrenewable resource constraints. Relaxing the latter constraints allows to visit a larger solution set and thus to simplify the evolutionary operators. On the other hand, we build the fitness function not on a priori grid of the bi-objective space, but on an adaptive one relying on clustering techniques. This proposed idea aims at more relevant fitness values. We show that a clustering-based fitness function can be an appealing feature in multi-objective evolutionary algorithms since it may promote diversity and avoid premature convergence of the algorithms. Clustering heuristics require certainly computation time, but they are still competitive with respect to classical niche formation multi-objective genetic algorithm.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 205 (2010)
Issue (Month): 1 (August)
Contact details of provider:
Web page: http://www.elsevier.com/locate/eor
Project scheduling Resource-constrained Multiple modes Evolutionary algorithms Bi-objective approach Clustering;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Karen Puttkammer & Rainer Kleber & Tobias Schulz & Karl Inderfurth, 2011. "Simultane Maschinenbelegungs- und Personaleinsatzplanung in KMUs anhand eines Fallbeispiels aus der Druckereibranche," FEMM Working Papers 110010, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
- Ramírez Palencia, Alberto E. & Mejía Delgadillo, Gonzalo E., 2012. "A computer application for a bus body assembly line using Genetic Algorithms," International Journal of Production Economics, Elsevier, vol. 140(1), pages 431-438.
- Van Peteghem, Vincent & Vanhoucke, Mario, 2014. "An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances," European Journal of Operational Research, Elsevier, vol. 235(1), pages 62-72.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.