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About

José Coelho holds a PhD in Systems Engineering from the Technical University of Lisbon in 2004. It is an Assistant Professor at the Open University in the Department of Science and Technology. Published 12 papers in international journals and more than 35 varied nature of resources in the open repository. In their professional activities interacted with 36 employees in co-authorships of scientific papers.

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Publications

2021

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

Authors
Guo, W; Vanhoucke, M; Coelho, J; Luo, J;

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

2020

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

Authors
Coelho, J; Vanhoucke, M;

Publication
Computers & Operations Research

Abstract

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

2018

An exact composite lower bound strategy for the resource-constrained project scheduling problem

Authors
Coelho, J; Vanhoucke, M;

Publication
Computers and Operations Research

Abstract
This paper reports on results for the well-known resource-constrained project scheduling problem. A branch-and-bound procedure is developed that takes into account all best performing components from literature, varying branching schemes and search strategies, using the best performing dominance rules and assembling these components into a unified search algorithm. A composite lower bound strategy that statically and dynamically selects the best performing bounds from literature is used to find optimal solutions within reasonable times. An extensive computational experiment is set up to determine the best combination of the various components used in the procedure, in order to benchmark the current existing knowledge on four different datasets from the literature. By varying the network topology, resource scarceness and the size of the projects, the computational experiments are carried out on a diverse set of projects. The procedure was able to find some new lower bounds and optimal solutions for the PSPLIB instances. Moreover, new best known results are reported for other, more diverse datasets that can be used in future research studies. The experiments revealed that even project instances with 30 activities cannot be solved to optimality when the topological structure is varied. © 2018 Elsevier Ltd