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Vanhoucke, Mario (10)

Coelho, José (2)Servranckx, Tom (2)Aouam, Tarik (1)Batselier, Jordy (1)Burgelman, Jeroen (1)De Causmaecker, Patrick (1)Eduardo Cooper Ordoñez, Robert (1)Leyman, Pieter (1)Maenhout, Broos (1)View MoreSubjectProject Scheduling (6)Alternative Subgraphs (2)Project Management (2)Activity Preemption (1)Critical Chain Method (1)Discrete Choice Models (1)Discrete Time Filters (1)Discrete Time/Cost Trade-off (1)Distribution Fitting (1)Earned Value Management (1)View MoreDate Issued
2019 (10)

Knowledge Domain/IndustryOperations & Supply Chain Management (10)Publication TypeJournal article with impact factor (8)Vlerick strategic journal article (2)

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An agency perspective for multi-mode project scheduling with time/cost trade-offs

Aouam, Tarik; Vanhoucke, Mario (Computers and Operations Research, 2019)

Project scheduling takes the perspective of a single decision-maker, where the owner is directly involved in the management and control of the project. In this paper, we study the multi-mode project scheduling problem from an agency perspective, where agency arises from the risk-averse contractor’s hidden effort, which influences the duration and cost of project activities. We formulate the owner’s problem of determining the optimal parameters of a linear incentive contract as a bi-level program, where the lower level is a multi-mode project scheduling problem with time/cost trade-offs, representing the contractor’s problem. Two benchmarks for the optimal contract are formulated, providing bounds on the expected total cost to the owner, and performance measures are defined accordingly. A stylized model of the owner’s problem is presented and solved in closed form for the simple case where an aggregate effort can be exerted at the project level, with restrictive assumptions on the variance of noise and the cost of effort. However, when effort is exerted at the activity level, solving the owner’s problem involves the solution of the multi-mode project scheduling problem. A numerical study for such situation is presented, which illustrates the trade-off between incentives and risk, and the effect of this trade-off on different project related costs. The findings from the stylized model and those from the numerical results of the presented example are compared in a computational experiment on 15 randomly generated projects.

Strategies for project scheduling with alternative subgraphs under uncertainty: Similar and dissimilar sets of schedules

Servranckx, Tom; Vanhoucke, Mario (European Journal of Operational Research, 2019)

In the resource-constrained project scheduling problem with alternative subgraphs (RCPSP-AS), we model alternative execution modes for work packages in the project. In contrast to the traditional RCPSP, the project network consists of different alternative work packages. To that purpose, the scheduling problem selects the best possible alternatives for the construction of the baseline schedule. On top of that, several back-up schedules are created in order to cope with unexpected changes along the project progress. In the presence of uncertainty, we can then switch between these alternative schedules at different decision moments in order to bring the project back on track. The alternative schedules are combined in a set of schedules that should be constructed by the project manager prior to project execution. We present a computational experiment to investigate the ability of using such a set of schedules in the presence of uncertainty during project execution. The experiments indicate that using a set of schedules outperforms the use of a single schedule, even when the uncertainty level is relatively low. The results also show that the composition of this schedule set is important. Therefore, a degree of schedule similarity is proposed to analyse this composition, and results show that a mix of similar and dissimilar schedules performs best. Finally, we show that the solution quality of each schedule in the set has an impact on the performance of the schedule switches given the project disruptions.

A statistical method for estimating activity uncertainty parameters to improve project forecasting

Vanhoucke, Mario; Batselier, Jordy (Entropy, 2019)

Just like any physical system, projects have entropy that must be managed by spending energy. The entropy is the project’s tendency to move to a state of disorder (schedule delays, cost overruns), and the energy process is an inherent part of any project management methodology. In order to manage the inherent uncertainty of these projects, accurate estimates (for durations, costs, resources, …) are crucial to make informed decisions. Without these estimates, managers have to fall back to their own intuition and experience, which are undoubtedly crucial for making decisions, but are are often subject to biases and hard to quantify. This paper builds further on two published calibration methods that aim to extract data from real projects and calibrate them to better estimate the parameters for the probability distributions of activity durations. Both methods rely on the lognormal distribution model to estimate uncertainty in activity durations and perform a sequence of statistical hypothesis tests that take the possible presence of two human biases into account. Based on these two existing methods, a new so-called statistical partitioning heuristic is presented that integrates the best elements of the two methods to further improve the accuracy of estimating the distribution of activity duration uncertainty. A computational experiment has been carried out on an empirical database of 83 empirical projects. The experiment shows that the new statistical partitioning method performs at least as good as, and often better than, the two existing calibration methods. The improvement will allow a better quantification of the activity duration uncertainty, which will eventually lead to a better prediction of the project schedule and more realistic expectations about the project outcomes. Consequently, the project manager will be able to better cope with the inherent uncertainty (entropy) of projects with a minimum managerial effort (energy).

Resource-constrained project scheduling with activity splitting and setup times

Vanhoucke, Mario; Coelho, José (Computers and Operations Research, 2019)

This paper presents a new solution algorithm to solve the resource-constrained project scheduling problem with activity splitting and setup times. The option of splitting activities, known as activity preemption, has been studied in literature from various angles, and an overview of the main contributions will be given. The solution algorithm makes use of a meta-heuristic search for the resource-constrained project scheduling problem (RCPSP) using network transformations to split activities in subparts. More precisely, the project network is split up such that all possible preemptive parts are incorporated into an extended network as so-called activity segments, and setup times are incorporated between the different activity segments. Due to the inherent complexity to solve the problem for such huge project networks, a solution approach is proposed that selects the appropriate activity segments and ignores the remaining segments using a boolean satisfiability problem solver, and afterwards schedules these projects to near-optimality with the renewable resource constraints. The algorithm has been tested using a large computational experiment with five types of setup times. Moreover, an extension to the problem with overlaps between preemptive parts of activities has been proposed and it is shown that our algorithm can easily cope with this extension without changing it. Computational experiments show that activity preemption sometimes leads to makespan reductions without requiring a lot of splits in the activities. Moreover, is shown that the degree of these makespan reductions depends on the network and resource indicators of the project instance.

A study of the critical chain project management method applied to a multiproject system

Eduardo Cooper Ordoñez, Robert; Vanhoucke, Mario; Coelho, José; Novaski, Olívio (Project Management Journal, 2019)

In 1997, Eliyahu Goldratt proposed a method called critical chain project management (CCPM) to minimize the inefficiencies identified in traditional project management. The project management community accepted the proposed method as a viable alternative. However, to allow its implementation with a multiproject system, more research was necessary. Seeking to identify the key factors that influence the performance of the multiproject system applying the CCPM method, we performed a case study. Logistic regression analysis showed that applying the CCPM method in a multiproject system allows for better time estimation of activities and facilitates the allocation of critical resources.

A heuristic procedure to solve the project staffing problem with discrete time/resource trade-offs and personnel scheduling constraints

Van Den Eeckhout, Mick; Maenhout, Broos; Vanhoucke, Mario (Computers & Operations Research, 2019)

Highlights • Project staffing with discrete time/resource trade-offs and calendar constraints. • An iterated local search procedure is proposed. • Different problem decomposition techniques are applied. Abstract When scheduling projects under resource constraints, assumptions are typically made with respect to the resource availability and activities are planned each with its own duration and resource requirements. In resource scheduling, important assumptions are made with respect to the staffing requirements. Both problems are typically solved in a sequential manner leading to a suboptimal outcome. We integrate these two interrelated scheduling problems to determine the optimal personnel budget that minimises the overall cost. Integrating these problems increases the scheduling flexibility, which improves the overall performance. In addition, we consider some resource demand flexibility in this research as an activity can be performed in multiple modes. In this paper, we present an iterated local search procedure for the integrated multi-mode project scheduling and personnel staffing problem. Detailed computational experiments are presented to evaluate different decomposition heuristics and comparison is made with alternative optimisation techniques.

A tabu search procedure for the resource-constrained project scheduling problem with alternative subgraphs

Servranckx, Tom; Vanhoucke, Mario (European Journal of Operational Research, 2019)

This paper investigates the resource-constrained project scheduling problem with alternative subgraphs (RCPSP-AS). In this scheduling problem, there exist alternative ways to execute subsets of activities that belong to work packages. One alternative execution mode must be selected for each work package and, subsequently, the selected activities in the project structure should be scheduled. Therefore, the RCPSP-AS consists of two subproblems: a selection and a scheduling subproblem. A key feature of this research is the categorisation of different types of alternative subgraphs in a comprehensive classification matrix based on the dependencies that exist between the alternatives in the project structure. As the existing problem-specific datasets do not support this framework, we propose a new dataset of problem instances using a well-known project network generator. Furthermore, we develop a tabu search that uses information from the proposed classification matrix to guide the search process towards high-quality solutions. We verify the overall performance of the metaheuristic and different improvement strategies using the developed dataset. Moreover, we show the impact of different problem parameters on the solution quality and we analyse the impact of distinct resource characteristics of alternatives on the selection process.

Tolerance limits for project control: An overview of different approaches

Vanhoucke, Mario (Computers and Industrial Engineering, 2019)

Monitoring the performance of projects in progress and controlling their expected outcome by taking corrective actions is a crucial task for any project manager. Project control systems are in use to quantify the project performance at a certain moment in time, and allow the project manager to predict the expected outcome if no action is taken. Consequently, these systems serve as mechanism that provide warning signals that tell the project manager when it is time to take corrective actions to bring the expected project outcome back on track. In order to trust these generated warning signals, the project manager has to set limits on the provide performance metrics that serve as thresholds for these actions.
This paper gives an overview of different approaches discussed in the literature to control projects using such actions thresholds. First and foremost, the paper discusses three classes of actions thresholds,ranging from very easy-to-use rules-of-thumb to more advanced statistical project control methodologies. Each of these tools have been the subject to research studies, each of which aim at showing their power to predict project problems during its progress. In addition, the paper will emphasize the fundamental different between statistical project control using tolerance limits and statistical process control for projects. Finally, three different quality metrics to evaluate the performance of such control methods are presented and discussed.

Computing project makespan distributions: Markovian PERT networks revisited

Burgelman, Jeroen; Vanhoucke, Mario (Computers and Operations Research, 2019)

This paper analyses the project completion time distribution in a Markovian PERT network. Several techniques to obtain exact or numerical expressions for the project completion time distribution are evaluated, with the underlying assumption that the activity durations are exponentially distributed random variables. We show that some of the methods advocated in the project scheduling literature are unable to solve standard datasets from the literature. We propose a framework to analyse the applicability, accuracy and sensitivity of different methods to compute project makespan distributions. An alternative data generation process is proposed to benchmark the different methods and the influence of project dataset parameters on the obtained results is extensively assessed.

The impact of solution representations on heuristic net present value optimization in discrete time/cost trade-off project scheduling with multiple cash flow and payment models

Leyman, Pieter; Van Driessche, Niels; Vanhoucke, Mario; De Causmaecker, Patrick (Computers and Operations Research, 2019)

The goal of this paper is to investigate the impact of different solution representations, as part of a metaheuristic approach, on net present value optimization in project scheduling. We specifically consider the discrete time/cost trade-off problem with net present value optimization and apply three payment models from literature. Each of these models determines the timing and size of cash flows from the contractor’s viewpoint. The contribution of this paper to literature is twofold.
First, we include cash flow distribution variants in the payment models, to also distinguish between different manners in which value is created and costs are incurred, as part of a general model for the contractor’s cash flow management. This general model is developed in order to explicitly include the progress of activities in the determination of the timing and size of payments to the contractor, which is currently lacking in literature.
Second, we employ an iterated local search framework to compare different solution representations and their corresponding local search and repair heuristics. The goal is to unambiguously show that the choice of a solution representation deserves a fair amount of attention, alongside the selection of appropriate diversification and intensification operators, even though this is not always the case in literature. Each part of the proposed algorithm is validated on a large dataset of test instances, generated to allow for a broad comparison of the solution representations. Our results clearly quantify the statistically significant differences between three types of representations for the project scheduling problem under study.

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