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A generic heuristic for multi-project scheduling problems with global and local resource constraints (RCMPSP)

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Abstract

This paper presents a novel algorithm to solve the multi-project scheduling problem with resource constraints (RCMPSP). The algorithm was tested with all the problems proposed in the multi-project scheduling problem library, which is the main reference to benchmark RCMPSP algorithms. Our analysis of the results demonstrates that this algorithm, in spite of its simplicity, outperforms other algorithms published in the library in 16% of the cases and holds the best result in 27% of the cases. These results, along with the fact that this is a general-purpose algorithm, make it a good choice to deal with limited time and resources in portfolio management.

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Notes

  1. Parallel schedule generation scheme (P-SGS) and minimum activity total slack (MIN-SLK) as a priority rule.

  2. www.mpsplib.com.

  3. http://www.mpsplib.com/ranking.php?method=&criterion=tms&j=&p=&g=.

  4. http://www.mpsplib.com.

  5. http://www.om-db.wi.tum.de/psplib/library.html.

  6. The results can be found under the name of PSGSMINSLK at MPSPLib: http://www.mpsplib.com/ranking.php?method=&criterion=tms&j=&p=&g=.

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Acknowledgements

This research has been partially financed by the project ABARNET (Agent-Based Algorithms for Railway NETworks optimization) financed by the Spanish Ministry of Economy, Industry and Competitiveness, with Grant DPI2016-78902-P, and the Computational Models for Industrial Management (CM4IM) project, funded by the Valladolid University General Foundation.

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Authors and Affiliations

  1. INSISOC Research Group, University of Valladolid, Paseo del Cauce, 59, 47011, Valladolid, Spain

    Félix Villafáñez, David Poza, Adolfo López-Paredes & Javier Pajares

  2. INSISOC Research Group, University of Burgos, C/ Villadiego s/n. 09001, Burgos, Spain

    Ricardo del Olmo

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  1. Félix Villafáñez
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Correspondence to David Poza.

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Communicated by V. Loia.

Appendix

Appendix

The following table compares the performance of P-SGS/MIN-SLK and the performance of the current leading algorithm for each one of the 140 problems in MPSPLib. For this aim, the table shows two entries per problem expect in those cases where P-SGS/MIN-SLK holds the best result, where only one entry is shown, Notice that the 38 (out of 140) RCMPSP problems in which PSGSMINSLK holds the best result in TMS are shown in shaded cells.

The name of the problems in MPSPLib are conveniently codified so that their names reflect the number and the size of the projects. For example, the first problem is named mp_j30_a10_nr1 meaning the following: a multi-project problem (mp) composed of 10 projects (a10) each of which has 30 activities (j30). The term nr1 is simply a reference to distinguish different problems with the same number of project and activities. For example, all of the first five problems have 10 projects and 30 activities (nr_1 to nr_5) which differ in the start dates of the projects and the number of global resources (2, 1, 2, 3 and 1, respectively). In the last 80 problems of the list, the suffix _AC is added to the name of the problem, which means that all the resources of that problem are global.

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Villafáñez, F., Poza, D., López-Paredes, A. et al. A generic heuristic for multi-project scheduling problems with global and local resource constraints (RCMPSP). Soft Comput 23, 3465–3479 (2019). https://doi.org/10.1007/s00500-017-3003-y

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