Showing papers by "Mario Vanhoucke published in 2016"

A comparative study of Artificial Intelligence methods for project duration forecasting

Abstract: We propose 5 AI methods for predicting a project's duration.A methodology including PCA, cross-validation and grid search is presented.A large computational experiment shows the good performance of the AI methods.A sensitivity analysis reveals the weakness of the proposed methods. This paper presents five Artificial Intelligence (AI) methods to predict the final duration of a project. A methodology that involves Monte Carlo simulation, Principal Component Analysis and cross-validation is proposed and can be applied by academics and practitioners. The performance of the AI methods is assessed by means of a large and topologically diverse dataset and is benchmarked against the best performing Earned Value Management/Earned Schedule (EVM/ES) methods. The results show that the AI methods outperform the EVM/ES methods if the training and test sets are at least similar to one another. Additionally, the AI methods report excellent early and mid-stage forecasting results. A robustness experiment gradually increases the discrepancy between the training and test sets and demonstrates the limitations of the newly proposed AI methods.

An Overview of Project Data for Integrated Project Management and Control

Abstract: In this paper, an overview is given of the project data instances available in the literature to carry out academic research in the field of integrated project management and control. This research field aims at integrating static planning methods and risk analyses with dynamic project control methodologies using the state-of-the-art knowledge from literature and the best practices from the professional project management discipline. Various subtopics of this challenging discipline have been investigated from different angles, each time using project data available in literature, obtained from project data generators or based on a sample of empirical case studies. This paper gives an overall overview of the wide variety of project data that are available and are used in various research publications. It will be shown how the combination of artificial data and empirical data leads to improved knowledge on and deeper insights into the structure and characteristics of projects useful for academic research and professional use. While the artificial data can be best used to test novel ideas under a strict design in a controlled academic environment, empirical data can serve as the necessary validation step to translate the academic research results into practical ideas, aiming at narrowing the bridge between the theoretical knowledge and practical relevance. A summary of the available project data discussed in this paper can be downloaded from http://www.projectmanagement.ugent.be/research/data VIDEO about paper: https://youtu.be/9VESaMeh3nI

Incentive contract design for projects : the owner׳s perspective

Abstract: Due to the adoption of more and more complex incentive contract structures for projects, designing the best contract for a specific situation has become an increasingly daunting task for project owners. Through the combination of findings from contracting literature with knowledge from the domain of project management, a quantitative model for the contract design problem is constructed. The contribution of this research is twofold. First of all, a comprehensive and quantitative methodology to analyse incentive contract design is introduced, based on an extensive review of the existing literature. Secondly, based on this methodology, computational experiments are carried out, which result in a set of managerial guidelines for incentive contract design. Our analysis shows that substantial improvements can often be attained by using contracts which include incentives for cost, duration as well as scope simultaneously. Moreover, nonlinear and piecewise linear formulae to calculate the incentive amounts are shown to improve both the performance and robustness across different projects.

Practical application and empirical evaluation of reference class forecasting for project management

Abstract: Traditionally, project managers produce cost and time forecasts by predicting the future course of specific events. In contrast, reference class forecasting (RCF) bypasses human judgment by basing ...

Optimised scheduling for weather sensitive offshore construction projects

Abstract: 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 as well as 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.

Empirical perspective on activity durations for project management simulation studies

Abstract: Simulation has played an important role in project-management studies of the last decades, but in order for them to produce practical results, a realistic distribution model for activity durations is indispensable. The construction industry often has needed historical records of project executions, to serve as inputs to the distribution models, but a clearly outlined calibration procedure is not always readily available, nor are their results readily interpretable. This study seeks to illustrate how data from the construction industry can be used to derive realistic input distributions. Therefore, the Parkinson simulation model with a lognormal core is applied to a large empirical dataset from the literature and the results are described. From a discussion of these results, an empirical classification of project executions is presented. Three possible uses are presented for the calibration procedure and the classification in project management simulation studies. These were validated using a case ...

An exact algorithm for an integrated project staffing problem with a homogeneous workforce

Abstract: When scheduling projects under resource constraints, assumptions are typically made with respect to the resource availability. In resource scheduling problems important assumptions are made with respect to the resource requirements. As projects are typically labour intensive, the underlying (personnel) resource scheduling problems tend to be complex due to different rules and regulations. In this paper, we aim to integrate these two interrelated scheduling problems to minimise the overall cost. For that purpose, we propose an exact algorithm for the project staffing with resource scheduling constraints. Detailed computational experiments are presented to evaluate different branching rules and pruning strategies and to compare the proposed procedure with other optimisation techniques.

On the use of multivariate regression methods for longest path calculations from earned value management observations

Abstract: This paper explores the use of multivariate regression methods for project schedule control within a statistical project control framework These multivariate regression methods monitor the activity level performance of an ongoing project from the earned value management/earned schedule (EVM/ES) observations that are made at a high level of the work breakdown structure (WBS) These estimates can be used to calculate the longest path in the project and to produce warning signals for project schedule control The effort that is spent by the project manager is thereby reduced, since a drill-down of the WBS is no longer required for every review period An extensive computational experiment was set up to test and compare four distinct multivariate regression methods on a database of project networks The kernel principal component regression method, when used with a radial base function kernel, was found to outperform the other presented regression methods

A scatter search for the extended resource renting problem

Abstract: In this paper, the extended Resource Renting Problem (RRP/extended) is presented. The RRP/extended is a time-constrained project scheduling problem, in which the total project cost is minimised. In the RRP/extended, this total project cost is determined by a number of extra costs, which are defined in this paper. These costs are based on the costs that are used in the traditional Resource Renting Problem and the Total Adjustment Cost Problem. Therefore, the RRP/extended represents a union of these two problems. To solve the RRP/extended, a scatter search is developed. The building blocks of this scatter search are specifically designed for the RRP/extended. We introduce two crossovers and an improvement method. The efficiency of these building blocks will be shown in the paper. Furthermore, a sensitivity analysis is presented in which the five costs have diverse values.

A Study on Complexity and Uncertainty Perception and Solution Strategies for the Time/Cost Trade-Off Problem

Abstract: In this paper, the Discrete Time/Cost Tradeoff Problem (DTCTP) is revisited in light of a student experiment. Two solution strategies are distilled from data of 444 participants and are structured by means of five building blocks, namely 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.

Stability of Earned Value Management - Do project characteristics influence the stability moment of the cost and schedule performance index

Abstract: Stability of the Cost Performance Index (CPI) and Schedule Performance Index (SPI (t) ) refers to the moment in the project life cycle at which the CPI and SPI (t) are accurate and constant. For a project manager a reliable CPI and SPI (t) is essential for taking corrective actions in time to keep the project on budget, planning and scope. The focus of this paper lies on identifying project characteristics which influence this moment of CPI and SPI (t) in the project life cycle. Both existing theories from earlier academic research and newly identified project characteristics are tested by using empirical data from nine projects executed by an engineering and consultancy company in the Netherlands. It is found that some project characteristics influence the moment of CPI and SPI (t) in the project lifecycle whereas other do not. The results of this paper contribute to the body of knowledge on EVM and might provide valuable information to project managers who consider to use EVM in their projects. The results of this research also point out new areas to explore the understanding of the stability of CPI and SPI (t) .

Integrated Project Management Sourcebook: A Technical Guide to Project Scheduling, Risk and Control

Abstract: This handbook is a unique, comprehensive resource for professional project managers and students in project management courses that focuses on the integration between baseline scheduling, schedule risk analysis and project control, also known as Dynamic Scheduling or Integrated Project Management and Control. It contains a set of more than 70 articles. Each individual article focuses on one particular topic and features links to other articles in this book, where appropriate. Almost all articles are accompanied with a set of questions, the answers to which are provided at the end of the book. This book is accompanied by and is based on the Project Management Knowledge Center (www.pmknowledgecenter.com), an online learning platform for Integrated Project Management.

Capital constraints and net present value optimization in project scheduling

Abstract: The resource–constrained project scheduling problem with discounted cash flows (RCPSPDC) is an extension of the well–known resource–constrained project scheduling problem (RCPSP). Both problems are subject to precedence and renewable resource constraints, but whereas the RCPSP aims to minimize the project duration, the RCPSPDC maximizes the project NPV based on a net cash in– or outflow (ci,net) associated with each activity. Conceptually, the RCPSPDC can be formulated as follows: