Resource-constrained Scheduling of a Real Project from the Construction Industry: A Comparison of Software Packages for Project Management

Resource-constrained Scheduling of a Real Project from the Construction Industry: A Comparison of Software Packages for Project Management N. Trautmann, P. Baumann Department of Business Administration, University of Bern, Bern, Switzerland (norbert.trautmann@pqm.unibe.ch, philipp.baumann@pqm.unibe.ch) Abstract - Commercial software packages for project management apply proprietary, heuristic procedures for resource-constrained scheduling. We analyze the scheduling performance of seven such packages. Three of them offer the possibility to select the priority rule to be used for the resource-constrained scheduling procedure. The project duration obtained strongly depends on this rule. Some packages know several thousand priority rules; in general, it is impossible to predict which rule provides the best result for a given project. By analyzing 1560 projects of an internationally recognized benchmark library, we propose a set of three rules for each package. We apply these rules to a real project from the construction industry. For each of the three packages, the project duration obtained by this set of rules is among the best results for all available rules, and is shorter than the project duration obtained by the packages which do not offer alternative priority rules. Keywords - Project management, resource-constrained scheduling, construction industry, software I. INTRODUCTION Projects are to be managed, e.g., in a company s information technology or new product development department. A project is a one-time endeavor which is dedicated to some objective and consists of a set of activities being interrelated by precedence constraints and requiring time and resources, e.g. personnel or equipment, for execution (see, e.g., Brucker et al. [2]). The project planning task includes the computation of the early and the late start schedule and the slack times of the activities (temporal scheduling) and the allocation of the scarce resources over time to the execution of the activities (resource allocation). In practice, software packages are widely used for this task (cf. Herroelen [5], Liberatore and Pollack-Johnson [14], Liberatore et al. [15], and White and Fortune [23]). In general, computing an optimal resource allocation is intractable; as a result, heuristic scheduling procedures are used. Which procedures are implemented in commercial software packages for project management is proprietary information. Various packages offer the possibility to control the resource allocation by a priority rule; in some packages, several thousand rules are implemented. For a given project, it is not obvious which priority rule will provide a good project schedule. A large variety of specific resource-allocation algorithms has been proposed in the literature; for an overview, we refer to Kolisch and Hartmann [10]. In contrast, the resource-constrained scheduling performance of commercial software packages for project management has been addressed by a few papers only. In these, the performance is analyzed by investigating instances of the resource-constrained project scheduling problem RCPSP, which can be described as follows. Given is a set of noninterruptible activities, a set of finish-start precedence constraints among these activities, and a set of scarce resources. During execution, each activity requires a given amount of time and a given amount of each resource. Sought is a schedule, i.e. a start time for each activity, such that the precedence constraints are satisfied, at no point in time does the total requirement for any resource exceed its capacity, and the total project duration is minimized. In simple terms, minimizing the project duration allows an organization to perform more projects with the same resource capacities, or to perform the same number of projects with reduced resource capacities. For a new product development project, minimal total project duration in addition enables short time-to-market. Johnson [6] analyzed the schedules obtained by seven software packages for 110 RCPSP instances generated by Patterson [19]. Kolisch and Hempel [11] and Kolisch [9] generated 160 RCPSP instances with 10, 20, and 30 activities as described by Kolisch et al. [13], and used them for analyzing seven software packages. Major drawbacks of both analyses are the fact that the considered software packages are out-of-date, and the limitation to small problem instances. The current standard benchmark in the field are the 1560 RCPSP instances from the project scheduling problem library PSPLIB (cf. Kolisch and Sprecher [12] and Kolisch et al. [13]) with 30, 60, and 120 activities, respectively. Mellentien and Trautmann [18] is the only published study of software packages for project management based on this benchmark; however, the systems included in that study are now outdated as well, and the study is limited to a descriptive analysis only. More descriptive analyses based on few problem instances have been presented by Farid and Manoharan [4], Kastor and Sirakoulis [7], Khattab and Søyland [8], Lova and Tormos [16], and Maroto and Tormos [17]. We also mention the general evaluations presented by Assad and Wasil [1] and De Wit and Herroelen [3]. In the present paper, we analyze the resourceconstrained scheduling capabilities of seven recent soft- 978-1-4244-4870-8/09/$26.00 2009 IEEE 628

ware packages for project management. We study the variation of the project durations obtained for the 1560 PSPLIB instances with each software package and, where available, alternative priority rules. Our study indicates major differences among the packages and the priority rules. For each package that includes alternative priority rules, we identify three candidate rules for computing a schedule with short project duration. We analyze the schedules obtained for a real construction project with these candidate rules. It turns out that the project duration obtained by the set of candidate rules is among the best results for all available rules. Moreover, the project duration obtained is shorter than the one obtained by the packages which do not offer any alternative priority rules. The analysis described in the present paper was restricted to software packages which work under Microsoft Windows, are able to read the data of a project from an ASCII file that we generated with external software, can be controlled using some macro language, and include a resource-constrained scheduling procedure. These requirements partly arise from the large number of problem instances that we have analyzed. As a consequence, we could use the software packages Acos Plus.1 (provider: ACOS Projektmanagement GmbH, version 8.9a, hereafter referred to as ACO) AdeptTracker (WangTuo Software, v3.12, ATP) CS Project Professional (CREST Software, v3.2, CSP) Microsoft Office Project 2007 (Microsoft Corporation, v12, MSP) Primavera P6 (Oracle Corporation, v6.1, PP6) Sciforma PS8 (Sciforma Corporation, v8.5, PS8) Turbo Project Professional (OfficeWork Software, version 4.00, TPP) The remainder of this paper is structured as follows. In Section II, we describe how the resource-constrained scheduling procedures of the software packages proceed in general, and we compare the schedules obtained for the construction project by the various software packages and priority rules. In Section III, we report on the results for the 1560 PSPLIB instances, and we state the sets of candidate rules. In Section IV, we analyze the results obtained for the construction project and the candidate rules. In Section V, we close the paper with some conclusions. II. PRIORITY-RULE BASED RESOURCE ALLOCA- TION WITH SOFTWARE PACKAGES FOR PROJECT MANAGEMENT In this section, we give an overview of the resourceconstrained scheduling procedures of the software packages for project management. Thereby, we use the construction project as an illustrative example. This project, which we refer to as the sample project, is described in the recent paper of Kastor and Sirakoulis [7]. The objective of the project is the construction of 96 houses; the single scarce resource is the supply of concrete. In total, there are 98 activities in the sample project. Which scheduling algorithms are implemented in software packages for project management is proprietary information; for that reason, our description is based on our experience from using the packages. As far as we can say, the resource-constrained scheduling procedures in such software packages use the following approach. First of all, the project data is entered or loaded from a file. If no start times have been determined for the activities yet (e.g. when a project is planned from scratch), the software package computes the early and the late start schedules, and schedules all activities according to the early start schedule. All software packages are able to represent the current schedule as a Gantt-chart and to display a synchronized resource profile that shows the amount of resource capacity required over time and indicates the periods in which the resource demand exceeds the resource capacity. A screenshot of these charts in Microsoft Project for our sample project is shown in Fig. 1. In most of the packages, the precedence relationships can be visualized in a network diagram of the activity-on-node type (cf. Fig. 2 for Microsoft Project and our sample project). Then, the resource-constrained scheduling procedure seeks for the first point in time where the resource demand exceeds the resource capacity. If such a resource overload is found, then all activities that (according to the current schedule) have not been completed at this point in time are scheduled at the earliest point in time that is feasible subject to the precedence relationships and the resource capacities. The scheduling sequence is determined by a priority rule; for details of this type of scheduling procedures, we refer to Brucker et al. [2]. The representation of the schedule computed by the resource-constrained scheduling procedure of Microsoft Project for our sample project is shown in Fig. 3. The ACO, CSP, and PP6 packages offer to the user the option to select that priority rule explicitly. The most extensive possibilities are provided by CSP and PP6; in both packages, the user can combine 14 priority rules in a multi-level hierarchy. We have tested 3150 priority rule combinations in CSP, and 196 priority rule combinations in PP6. In ACO, a single-level rule is applied; here, the user can choose between 8 priority rules. We have tested all of them. The packages ATP, MSP, PS8, and TPP do not offer alternative priority rules for the resourceconstrained scheduling procedure. Table 1 shows the project durations that we obtained for our sample project; Table 1 Project durations for the sample project under various priority rules Shortest Mean Longest ACO 709 728.75 753 ATP 744 744.00 744 CSP 692 776.65 805 MSP 744 744.00 744 PP6 691 813.52 918 PS8 711 711.00 711 TPP 832 832.00 832 629

apply when, e.g. due to time constraints, she cannot try all available rules. III. CANDIDATE RULES FOR MINIMIZING THE PROJECT DURATION Fig. 1. MSP: early start schedule for the sample project In this section, first we summarize the results of an analysis of the resource-constrained scheduling capabilities of the software packages which is based on the 1560 projects with 30, 60, and 120 activities from the test set PSPLIB (test set J30, J60, and J120 hereafter); details about this analysis can be found in Trautmann and Baumann [20], [21], and [22]. Second, we devise a set of candidate rules that may be used within each of the packages ACO, CSP, and PP6 for computing schedules with short project duration. A. Analysis of the PSPLIB instances Fig. 2. MSP: part of the sample-project network Fig. 3. MSP: result of the resource-constrained scheduling procedure for the sample project the columns refer to the shortest, the mean, and the longest project durations that we obtained by selecting alternative priority rules. We observe major differences among the various software packages with respect to all three values. Moreover, we notice a considerable gap between the shortest and the longest project duration obtained for the various priority rules within ACO, CSP, and PP6. The shortest, but also the by far longest project durations are obtained by PP6 and CSP, i.e., the two packages offering the most extensive variety of priority rules to choose from. This gives rise to the question which priority rule a user should In order to evaluate the schedules obtained by the software packages, we compared them to the project durations in the optimal schedules (J30 set) and in the best known feasible schedules (J60 and J120 set), respectively, as reported on May 18, 2008 on the page http://129.187.106.231/psplib. These schedules were obtained by state-of-the-art algorithms from the literature. We loaded each of the 1560 projects into each of the seven software packages, specifying it as a single project with activities of constant duration and resources of 24/7 availability, and applied the resource-constrained scheduling procedure of the software package. We mention that for 190 instances, the resource-constrained scheduling procedure of Acos Plus.1 created cyclic precedence relationships and returned infeasible schedules; we did not take these schedules into account. For all other projects and software packages, we always obtained a feasible schedule. The CPU time required by the various software packages for the resource-constrained scheduling of a single project never exceeded 30 seconds on a standard PC. For none of the 1560 instances, any software package did compute a schedule with shorter project duration than in the reference schedule. Table 2 shows the means of the relative increase of the project duration under the assumption that for each of the 1560 instances the user selects a rule which results in Table 2 Mean relative schedule growth for 1560 PSPLIB projects under various priority rules Shortest Mean Longest ACO 7.08% 12.13% 19.14% ATP 8.33% 8.33% 8.33% CSP 8.34% 16.36% 23.12% MSP 9.44% 9.44% 9.44% PP6 5.69% 21.57% 40.51% PS8 7.85% 7.85% 7.85% TPP 15.09% 15.66% 16.22% 630

the shortest or the longest project duration, respectively, of the software package for that instance. Additionally, Table 2 shows the mean relative project duration increase over all rules and projects that we have analyzed. The results indicate that none of the tested software packages is currently competitive with the best state-ofthe-art algorithms from the literature. Similar to the case of the sample project discussed in Section II, the shortest, but also the by far longest project durations are computed by the PP6 package. Again, for the ACO, CSP, and PP6 packages, the schedule growth strongly depends on the priority rule selected. The variation of the project durations obtained by the TPP package is caused by two alternative modes of the resource-allocation procedure; for details, we refer to Trautmann and Baumann [21]. B. Sets of candidate rules for short project durations Next, we devise the set of candidate rules for each of the software packages ACP, CSP, and PP6. To this end, we computed the mean relative deviation of the project duration obtained from the reference value for each individual priority rule. A single rule may not be sufficient for all kinds of projects; therefore, for each software package we selected three rules A, B, and C as follows. Rule A is the one for which we obtained the lowest mean relative deviation of the project duration. Rule B is the rule for which we obtained the second-lowest mean relative deviation. In order to stimulate the generation of structurally different schedules, for the selection of rule B we considered only rules which differ from rule A in the first level. For the selection of rule C, we proceeded analogously. We obtained the following sets of candidate rules for the ACO package. Rule A: total number of successors Rule B: free float Rule C: total number of predecessors and successors. For the CSP package, we obtained the following set of candidate rules. Rule A: CARLO (a proprietary cost and resource leveling optimization algorithm) Rule B: late finish (1st level), duration (2nd level), total float (3rd level) Rule C: start-baseline (1st), late finish (2nd) For the PP6 package, we obtained the following set of candidate rules. Rule A: late start (1st), late finish (2nd) Rule B: late finish (1st), duration (2nd) Rule C: free float (1st), late start (2nd) Table 3 Project durations for the sample project under the candidate rules Rule A Rule B Rule C ACO 709 753 709 CSP 692 788 788 PP6 717 708 726 For both the ACO and the CSP package, respectively, the project duration obtained with candidate rule A is the shortest over all rules that we have analyzed. For the PP6 package, the shortest project duration is obtained with candidate rule B; that duration is 2.5% longer than the shortest duration obtained with all rules that we have analyzed. For all three packages, however, the shortest project duration obtained with the set of candidate rules is shorter than for any of the packages which do not offer alternative priority rules. V. CONCLUSIONS In this paper, we have studied the resourceconstrained scheduling capabilities of seven commercial software packages for project management. Their basic approach is to start from the early start schedule, and to remove successively all resource overloads by delaying involved activities, which are categorized using a priority rule. Even if all packages use the same kind of approach, the analysis of a real project from the construction industry has revealed that the packages compute considerably different project durations. The priority rule used in the scheduling procedure strongly influences the length of the resulting schedule. The analysis of 1560 projects from the internationally recognized problem library PSPLIB has shown that for the resource- and precedence-constrained project scheduling problem RCPSP, the project durations computed by any of these packages are noticeably longer than in the best known feasible schedules. For the three software packages which offer alternative priority rules, we have devised sets of candidate rules that we propose for computing schedules with short project durations. We have verified the appropriateness of these sets of candidate rules by means of the construction project. Important areas for future research are the modeling capabilities of such software packages for project management, and the resource-constrained scheduling capabilities for corresponding project scenarios. A starting point may be the consideration of resource calendars that map holidays and week-ends or time-varying resource capacities. IV. APPLICATION TO THE CONSTRUCTION PROJECT In this section, we apply the sets of candidate rules devised in Section III to our sample project introduced in Section II. Table 3 lists the durations obtained for the relevant software packages and the candidate rules. ACKNOWLEDGMENT We would like to thank Kleanthis Sirakoulis for providing us the data of the construction project. 631

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