Wauters, Mathieu; Vanhoucke, Mario (Project Management Journal, 2016)
In this article, the Discrete Time/Cost Tradeoff Problem (DTCTP) is revisited in light of a student experiment. Two solution strategies are distilled from the data of 444 participants and are structured by means of five building blocks: focus, activity criticality, ranking, intensity, and action. The impact of complexity and uncertainty on the cost objective is quantified in a large computational experiment. Specific attention is allocated to the influence of the actual and perceived complexity and uncertainty and the cost repercussions when reality and perception do not coincide.
Maenhout, Broos; Vanhoucke, Mario (Annals of Operations Research, 2017)
In the integrated project scheduling and personnel staffing problem the project activities are scheduled and simultaneously a staffing plan is composed to carry out a single project. In this way, the project schedule that leads to the staffing plan with minimum cost is determined. In this paper, we evaluate different scheduling policies and practices for different personnel resource types. We examine the impact on the staffing cost when the personnel resources are scheduled in a cyclic versus a non-cyclic manner for different (days on, days off)-patterns. Furthermore, the impact of introducing more flexible resource types, such as overtime and temporary help, is explored in relationship with the activity resource demand variability. Computational results show that non-cyclic scheduling leads to a considerable lower staffing cost under all circumstances compared to cyclic scheduling. However, despite the tractability of the resource requirements, flexible temporary resources are essential on top of the regular personnel resources to respond to the variability in demand. The addition of overtime on a strategic staffing level only marginally decreases the personnel cost.
Kerkhove, Louis-Philippe; Vanhoucke, Mario (Omega - International Journal of Management Science, 2017)
The significant lead times and costs associated with materials and equipment in combination with intrinsic and weather related variability render the planning of offshore construction projects highly complex. Moreover, the way in which scarce resources are managed has a profound impact on both the cost and the completion date of a project. Hence, schedule quality is of paramount importance to the profitability of the project. A prerequisite to the creation of good schedules is the accuracy of the procedure used to estimate the project outcome when a given schedule is used. Because of the systematic influence of weather conditions, traditional Monte Carlo simulations fail to produce a reliable estimate of the project outcomes. Hence, the first objective of this research is to improve the accuracy of the project simulation by creating a procedure which includes both uncertainty related to the activities and an integrated model of the weather conditions. The weather component has been designed to create realistically correlated wind- and weather conditions for operationally relevant time intervals. The second objective of this research is to optimise the project planning itself by using both general meta-heuristic optimisation approaches and dedicated heuristics which have been specifically designed for the problem at hand. The performance of these heuristics is judged by the expected net present value of the project. The approach presented in this paper is tested on real data from the construction of an offshore wind farm off the Belgian coast and weather data gathered by the Flanders Marine Institute using measuring poles in the North Sea.
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.
Van Peteghem, Vincent; Vanhoucke, Mario (European Journal of Operational Research, 2014)
In this paper, an overview is presented of the existing metaheuristic solution procedures to solve the multi-mode resource-constrained-project scheduling problem, in which multiple execution modes are available for each of the activities of the project. A fair comparison is made between the different metaheuristic algorithms on the existing benchmark datasets and on a newly generated dataset. Computational results are provided and recommendations for future research are formulated.
In this paper the Resource Renting Problem with Overtime (RRP/overtime) is presented. The RRP/overtime is a new problem in which the assumptions of the basic RRP are combined with the possibility to schedule (parts of) activities during overtime. The addition of this extension increases the applicability of the RRP to real world problems. This paper also presents a solution technique for this extension of the resource renting problem. The solution procedure uses a scatter search heuristic to optimize a priority list, which is then in turn used by a schedule generation scheme (PatSGS). A variation on this schedule generation scheme is also used in dedicated local search procedures. The third contribution of this research is a new lower bound for the RRP/overtime problem, which is used to evaluate the results of the proposed heuristic solution method.
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.
Vanhoucke, Mario (Frontiers of Engineering Management, 2018)
This paper is an invited request to describe the main research challenges in the domain of resource-constrained project scheduling. The paper is split up in three parts. In today’s challenges, research endeavors that have received a significant, but still not enough, attention have been described. In tomorrow’s research challenges, some promising research avenues for future research have been given. Finally, in yesterday’s challenge, a research topic that started decades ago, is said to have still a huge potential in tomorrow’s research agenda. This paper does not intend to give a full literature overview, nor a summary of all possible research paths. Instead, it is inspired from the author’s experience in academic research and practical consultancy and it serves as a personal opinion on a non-exhaustive set of promising research avenues, rather than giving a full literature-based advice for future research directions.
Leyman, Pieter; Vanhoucke, Mario (European Journal of Operational Research, 2017)
In this paper, we study the capital-constrained project scheduling problem with discounted cash flows (CCPSPDC) and the capital- and resource-constrained project scheduling problem with discounted cash flows (CRCPSPDC). The objective of both problems is to maximize the project net present value (NPV), based on three cash flow models. Both problems include capital constraints, which force the project to always have a positive cash balance. Hence, it is crucial to schedule activities in such an order that sufficient capital is available.The contribution of this paper is threefold. First, we propose three distinct cash flow models, which affect the capital availability during the project. Second, we introduce two new schedulers to improve capital feasibility, one for the CCPSPDC and one for the CRCPSPDC. The schedulers focus on delaying sets of activities, which cause cash outflows to be received at later time instances, in order to reduce capital shortages. Both schedulers are implemented as part of three metaheuristics from literature, in order to compare the metaheuristics' performance. Two penalty functions have been included, one to improve capital feasibility and another to improve deadline feasibility. Third, the proposed procedure has been tested on a large dataset and the added value of the schedulers has been validated. Managerial insights are provided with respect to the impact of key parameters.
Verbeeck, Cédric; Van Peteghem, Vincent; Vanhoucke, Mario; Vansteenwegen, Pieter; Aghezzaf, El Houssaine (OR Spectrum - Quantitative Approaches in Management, 2017)
In this paper, a metaheuristic solution procedure for the Time-Constrained Project Scheduling Problem is proposed, in which additional resources can be temporarily allocated to meet a given deadline. The problem consists of determining a schedule such that the project is completed on time and that the total additional cost for the resources is minimized. For this problem, an artificial immune system is proposed, in which each solution is represented by a vector of activity start times. A local search procedure, which tries to shift cost causing activities, is applied to each population schedule. Computational experiments are applied to modified resource-constrained project scheduling problem benchmark instances and reveal promising results.
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