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Publications

Publications by José Coelho

2017

Prazerosa – Interactive Reading Chair

Authors
Gaspar, RMA; Coelho, JPFdS; Bastos, GML;

Publication
International Journal of Creative Interfaces and Computer Graphics

Abstract

2018

A tool to test and validate algorithms for the resource-constrained project scheduling problem

Authors
Vanhoucke, M; Coelho, J;

Publication
Computers and Industrial Engineering

Abstract
In a paper written by by Vanhoucke et al. (2016), an overview of artificial and empirical project databases has been given for integrated project management and control. These databases are collections of the most well-known and widespread data instances available in literature for the construction of a baseline schedule, the analysis of schedule risk or the use for project control. The current paper serves as a follow-up study to further elaborate on the use of these data instances, and to give researchers an incentive to use these datasets for their research on the development and validation of new algorithms for project scheduling. Therefore, unlike the general focus of the previous paper on baseline scheduling, schedule risk analysis and project control, the focus on the current paper is restricted to resource-constrained project scheduling. The intention of this follow-up overview is fourfold. First and foremost, a procedure is proposed to facilitate the reporting of best known solutions for the well-known single- and multi-mode resource-constrained project scheduling problem to minimize the project makespan. Secondly, the paper reports our best known solutions we obtained so far, and reflects on the network and resource parameters that increase the project complexity. In doing so, areas to focus on for future research are detected, and an attempt to define hard problem instances is given. Thirdly, a new dataset is presented for the resource-constrained project scheduling problem that is much more diverse in both the network topology and resource scarceness and will enable the future researcher to develop algorithms to solve a wider range of project problems. Finally, the paper also adds some links to tutorials and other relevant information to stimulate researchers to download the data and update best known solutions once available. © 2018 Elsevier Ltd

2019

A Study of the Critical Chain Project Management Method Applied to a Multiproject System

Authors
Cooper Ordonez, REC; Vanhoucke, M; Coelho, J; Anholon, R; Novaski, O;

Publication
Project Management Journal

Abstract
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. © 2019 Project Management Institute, Inc.

2019

Resource-constrained project scheduling with activity splitting and setup times

Authors
Vanhoucke, M; Coelho, J;

Publication
Computers & Operations Research

Abstract

2020

Going to the core of hard resource-constrained project scheduling instances

Authors
Coelho, J; Vanhoucke, M;

Publication
Computers & Operations Research

Abstract

2021

Automatic detection of the best performing priority rule for the resource-constrained project scheduling problem

Authors
Guo, WK; Vanhoucke, M; Coelho, J; Luo, JY;

Publication
Expert Systems with Applications

Abstract
Priority rules are applied in many commercial software tools for scheduling projects under limited resources because of their known advantages such as the ease of implementation, their intuitive working, and their fast speed. Moreover, while numerous research papers present comparison studies between different priority rules, managers often do not know which rules should be used for their specific project, and therefore have no other choice than selecting a priority rule at random and hope for the best. This paper introduces a decision tree approach to classify and detect the best performing priority rule for the resource-constrained project scheduling problem (RCPSP). The research relies on two classification models to map project indicators onto the performance of the priority rule. Using such models, the performance of each priority rule can be predicted, and these predictions are then used to automatically select the best performing priority rule for a specific project with known network and resource indicator values. A set of computational experiment is set up to evaluate the performance of the newly proposed classification models using the most well-known priority rules from the literature. The experiments compare the performance of multi-label classification models with multi-class classification models, and show that these models can outperform the average performance of using any single priority rule. It will be argued that this approach can be easily extended to any extension of the RCPSP without changing the methodology used in this study. © 2020 Elsevier Ltd

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