Showing papers by "Mario Vanhoucke published in 2020"

Resource-constrained multi-project scheduling: benchmark datasets and decoupled scheduling

Abstract: In this paper, we propose a new dataset for the resource-constrained multi-project scheduling problem and evaluate the performance of multi-project extensions of the single-project schedule generation schemes. This manuscript contributes to the existing research in three ways. First, we provide an overview of existing benchmark datasets and classify the multi-project literature based on the type of datasets that are used in these studies. Furthermore, we evaluate the existing summary measures that are used to classify instances and provide adaptations to the data generation procedure of Browning and Yassine (J Scheduling 13(2):143-161, 2010a). With this adapted generator we propose a new dataset that is complimentary to the existing ones. Second, we propose decoupled versions of the single-project scheduling schemes, building on insights from the existing literature. A computational experiment shows that the decoupled variants outperform the existing priority rule heuristics and that the best priority rules differ for the two objective functions under study. Furthermore, we analyse the effect of the different parameters on the performance of the heuristics. Third, we implement a genetic algorithm that incorporates specific multi-project operators and test it on all datasets. The experiment shows that the new datasets are challenging and provide opportunities for future research.

Integrating Corrective Actions in Project Time Forecasting Using Exponential Smoothing

Abstract: Earned value management (EVM) and earned duration management (EDM) are established methodologies to monitor the project performance during execution. These methods serve as a basis to forec...

A project buffer and resource management model in energy sector; a case study in construction of a wind farm project

Abstract: This study aims to introduce an efficient project buffer and resource management (PBRM) model for project resource leveling and project buffer sizing and controlling of project buffer consumption of a wind power plant project to achieve a more realistic project duration.,The methodology of this research consists of three main phases. In the first phase of the research methodology, resource leveling is done in the project and resource conflicts of activities are identified. In the second phase, the project critical chain is determined, and the appropriate size of the project buffer is specified. In the third phase of the methodology, buffer consumption is controlled and monitored during the project implementation. After using the PBRM method, the results of this project were compared with those of the previous projects.,According to the obtained results, it can be concluded that using PBRM model in this wind turbine project construction, the project duration became 25 per cent shorter than the scheduled duration and also 29 per cent shorter than average duration of previous similar projects.,One of the major problems with projects is that they are not completed according to schedule, and this creates time delays and losses in the implementation of projects. Today, as projects in the energy sector, especially renewable projects, are on the increase and also we are facing resource constraint in the implementation of projects, using scheduling techniques to minimize delays and obtain more realistic project duration is necessary.,This research was carried out in a wind farm project. In spite of the initial plan duration of 142 days and average duration of previous similar projects of 146 days, the project was completed in 113 days.,This paper introduces a practical project buffer and resource management model for project resource leveling, project buffer sizing and buffer consumption monitoring to reach a more realistic schedule in energy sector. This study adds to the literature by proposing the PBRM model in renewable energy sector.

Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information

Abstract: Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions’ performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation.

Multimode time-cost-robustness trade-off project scheduling problem under uncertainty

Abstract: The time/cost trade-off problem is a well-known project scheduling problem that has been extensively studied. In recent years, many researchers have begun to focus on project scheduling problems under uncertainty to cope with uncertain factors, such as resource idleness, high inventory, and missing deadlines. To reduce the disturbance from uncertain factors, the aim of robust scheduling is to generate schedules with time buffers or resource buffers, which are capped by project makespan and project cost. This paper addresses a time-cost-robustness trade-off project scheduling problem with multiple activity execution modes under uncertainty. A multiobjective optimization model with three objectives (makespan minimization, cost minimization, and robustness maximization) is constructed and three propositions are proposed. An epsilon-constraint method-based genetic algorithm along with three improvement measures is designed to solve this NP-hard problem and to develop Pareto schedule sets, and a large-scale computational experiment on a randomly generated dataset is performed to validate the effectiveness of the proposed algorithm and the improvement measures. The final sensitivity analysis of three key parameters shows their distinctive influences on the three objectives, according to which several suggestions are given to project managers on the effective measures to improve the three objectives.

Mode generation rules to define activity flexibility for the integrated project staffing problem with discrete time/resource trade-offs

Abstract: In this paper, we study the project staffing problem with discrete time/resource trade-offs to minimise the personnel staffing budget. This staffing problem embeds activity scheduling flexibility by incorporating the project scheduling problem into the personnel staffing problem to improve the quality of the staffing plan. In addition, we introduce extra demand scheduling flexibility resulting from the design of alternative execution modes for the activities, modelled via discrete time/resource trade-offs. In this way, the project manager is able to decide on the team size and duration for every activity. We propose a two-stage methodology to first design specific alternative activity modes using heuristic rules-of-thumb and subsequently we assess the resulting quality, i.e. the staffing cost, via the integrated composition of the project schedule and associated staffing plan. The heuristic mode generation rules determine the selection of a limited set of relevant activities and modes. The computational results show that the impact of these heuristic generation rules on the staffing budget is dependent on the defined relation between different activity alternatives for a particular activity and on the estimated characteristics of the activity base modes. We show that by focusing on a particular well-chosen subset of activity alternatives or on a particular subset of activities, high-quality solutions realising most of the potential cost improvements resulting from the discrete time/resource trade-offs can be derived with a reduced effort.

A Simulation Study on the Impact of Activity Crashing on the Project Duration and Cost under Different Budget Release Scenarios

Abstract: The main goal of project control is to identify project opportunities or problems during project execution, such that corrective actions can be taken to bring the project in danger back on track when necessary. In this study, we define different scenarios to allocate the limited budget used for the cost of activity execution, delays, and corrective actions, according to the timing and amount of the budget release. A large computational experiment is conducted on real-life project data to evaluate the performance of each scenario. The results show that both the timing and amount of the budget release have an effect on project performance.