Resource-allocation capabilities of commercial project management software. An experimental analysis

Trautmann, Norbert; Baumann, Philipp (2009). Resource-allocation capabilities of commercial project management software. An experimental analysis. In: Kacem, Imed (ed.) Proceedings of the 39th International Conference on Computers and Industrial Engineering, Troyes 6.-9.7.2009 (pp. 1143-1148). New York: Institute of Electrical and Electronics Engineers IEEE 10.1109/ICCIE.2009.5223881

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When project managers determine schedules for resource-constrained projects, they commonly use commercial project management software packages. Which resource-allocation methods are implemented in these packages is proprietary information. The resource-allocation problem is in general computationally difficult to solve to optimality. Hence, the question arises if and how various project management software packages differ in quality with respect to their resource-allocation capabilities. None of the few existing papers on this subject uses a sizeable data set and recent versions of common software packages. We experimentally analyze the resource-allocation capabilities of Acos Plus.1, AdeptTracker Professional, CS Project Professional, Microsoft Office Project 2007, Primavera P6, Sciforma PS8, and Turbo Project Professional. Our analysis is based on 1560 instances of the precedence- and resource-constrained project scheduling problem RCPSP. The experiment shows that using the resource-allocation feature of these packages may lead to a project duration increase of almost 115% above the best known feasible schedule. The increase gets larger with increasing resource scarcity and with increasing number of activities. We investigate the impact of different complexity scenarios and priority rules on the project duration obtained by the software packages. We provide a decision table to support managers in selecting a software package and a priority rule.

Item Type:

Conference or Workshop Item (Paper)


03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Financial Management > Professorship for Quantitative Methods in Business Administration

UniBE Contributor:

Trautmann, Norbert and Baumann, Philipp


600 Technology > 650 Management & public relations




Institute of Electrical and Electronics Engineers IEEE




Juliana Kathrin Zurbrügg

Date Deposited:

04 Oct 2013 15:15

Last Modified:

28 Jan 2020 13:47

Publisher DOI:


Web of Science ID:




URI: (FactScience: 198386)

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