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Sobre

José Coelho é doutorado em Engenharia de Sistemas pela Universidade Técnica de Lisboa em 2004. É Professor Auxiliar na Universidade Aberta, no Departamento de Ciências e Tecnologia. Publicou 12 artigos em revistas internacionais e mais de 35 recursos de natureza variada, no repositório aberto. Nas suas atividades profissionais interagiu com 36 colaboradores em coautorias de trabalhos científicos.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    José Coelho
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 maio 2014
001
Publicações

2021

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

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

Publicação
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

2021

An analysis of network and resource indicators for resource-constrained project scheduling problem instances

Autores
Vanhoucke, M; Coelho, J;

Publicação
Comput. Oper. Res.

Abstract
In the past decades, the resource on the resource-constrained project scheduling problem (RCPSP) has grown rapidly, resulting in an overwhelming amount of solution procedures that provide (near)-optimal solutions in a reasonable time. Despite the rapid progress, little is still known what makes a project instance hard to solve. Inspired by a previous research study that has shown that even small instances with only up to 30 activities is sometimes hard to solve, the current study provides an analysis of the project data used in the academic literature. More precisely, it investigates the ability of four well-known resource indicators to predict the hardness of an RCPSP instance. The study introduces a new instance equivalence concept to show that instances might have very different values for their resource indicators without changing any possible solution for this instance. The concept is based on four theorems and a search algorithm that transforms existing instances into new equivalent instances with more compact resources. This algorithm illustrates that the use of resource indicators to predict the hardness of an instance is sometimes misleading. In a set of computational experiment on more than 10,000 instances, it is shown that the newly constructed equivalent instances have values for the resource indicators that are not only different than the values of the original instances, but also often are better in predicting the hardness the project instances. It is suggested that the new equivalent instances are used for further research to compare results on the new instances with results obtained from the original dataset. © 2021 Elsevier Ltd

2020

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

Autores
Coelho, J; Vanhoucke, M;

Publicação
Computers & Operations Research

Abstract

2019

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

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

Publicação
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

Autores
Vanhoucke, M; Coelho, J;

Publicação
Computers & Operations Research

Abstract