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Sobre

Sobre

João Bastos é Professor Adjunto do Departamento de Engenharia Mecânica do ISEP - Politécnico do Porto. É licenciado em Engenharia Mecânica pela FEUP, é Mestre em Engenharia Electrotécnica e Computadores no ramo de Informática Industrial na FEUP, e obteve o Doutoramento do Programa Doutoral em Engenharia Industrial e Gestão - PRODEIG na FEUP na área do planeamento distribuído. As suas áreas de interesse são: Gestão de Redes de Fornecimento; Planeamento Distribuído; Optimização de sistemas produtivos. É investigador do Instituto Nacional de Sistemas e Computadores do Porto - INESC TEC Laboratório Associado e participa em vários projectos de investigação. Participa e publica em conferências internacionais e nacionais bem como em revistas.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    João Bastos
  • Cargo

    Investigador Auxiliar
  • Desde

    01 março 1999
005
Publicações

2024

Comparative Analysis of Multicriteria Decision-Making Methods for Bus Washing Process Selection: A Case Study

Autores
Avila, P; Mota, A; Oliveira, E; Castro, H; Ferreira, LP; Bastos, J; Nuno, OF; Moreira, J;

Publicação
JOURNAL OF ENGINEERING

Abstract
Water is at the core of sustainable development, and its use for human activities, including vehicle washing, should be done in a sustainable way. There are several technical solutions for washing buses offering different performances, making it difficult to choose the one that best meets the requirements of each specific case. The literature on the topic hardly analyzes the choice of the best technical solution for washing buses and does not apply and compare the results of different multicriteria decision-making (MCDM) methods for the problem. The unique information available is from the different suppliers in the market. Whereby, this work intends to give a technical-scientific contribution to fulfill this gaps. Therefore, the main objectives of this work are (1) to select the best sustainable technical solutions for washing buses depending on the specific conditions for a case study and (2) to analyze how different multicriteria decision-making methods behave in the selection process. To achieve these objectives, the problem was approached as a case study in a public transport company in Portugal and the methodology followed the next steps: started with the identification of the different types of commercial technical solutions for washing buses; the company's experts selected four main criteria: water consumption, operating costs, quality of washing, and time spent; the criteria weights were determined using the fuzzy-AHP method; then four representative MCDM methods were selected, namely, AHP, ELECTRE, TOPSIS, and SMART; the ranks obtained for the four methods were compared; and a sensitivity analysis was performed. Considering the input data for the criteria and their weights, the results for all the methods showed that the best and the worst solution was the same, mobile portico with a brush and porticoes with three brushes, respectively. Furthermore, the results of the sensitivity analysis performed with disturbances for the weights of each criterion presented that the results are slightly affected and the similarity in rankings for the four MCDM methods was validated by Spearman's rank correlation coefficient (rs) and Kendall's coefficient of concordance (W). Considering these results, the SMART method, the less complex one, showed no difference from the others. For that reason, simple methods, such as SMART, in line with other works in the literature perform well in most cases. As a final remark of this work, it can be said that the methodology employed in this project can also be deemed applicable to other similar companies seeking technical solutions for bus or truck washing. Furthermore, the application of the SMART method, the less complex one and the most understandable for people, showed no difference from the others, being able to be applied in similar situations.

2023

Bat Algorithm for Discrete Optimization Problems: An Analysis

Autores
Sousa, B; Guerreiro, R; Santos, AS; Bastos, JA; Varela, LR; Brito, MF;

Publicação
Lecture Notes in Mechanical Engineering

Abstract
In this article the application of the discrete version of the bat algorithm to flowshop scheduling problems is presented and compared with Simulated Annealing, Local Search, as well as versions of each that start from constructive heuristics (Palmer and CDS). Bat algorithm is a novel metaheuristic, developed for continuous problems that has shown exceptional results. This paper intends to assess its effectiveness and efficiency for discrete problems when compared with other optimization techniques, including Simulated Annealing and Local Search, whose results are already proven. First, it was developed a literature review about those algorithms, then they were implemented in VBA with Microsoft Excel. Once implemented, the parameterization was carried out, ensuring an adequate application of the algorithms before they can be compared. Then, the methods were applied for 30 normally distributed instances, in order to draw broader conclusions. Finally, a statistical evaluation was carried out and concluded the inferiority of the Local Search in relation to the metaheuristics and the superiority of the hybrid version of the Bat Algorithm with CDS in relation to Simulated Annealing, with significantly better solutions, in an equal computation time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

Firefly and Cuckoo Search Algorithm for Scheduling Problems: A Performance Analysis

Autores
Moreira, C; Costa, C; Santos, AS; Bastos, JA; Varela, LR; Brito, MF;

Publicação
Lecture Notes in Mechanical Engineering

Abstract
Meta-heuristics are some of the best-known techniques to approach hard optimization problems, however, there are still questions about what makes some meta-heuristics better than others in a specific problem. This paper presents an analysis of the Firefly and Cuckoo Search Algorithm, such as others meta-heuristics. In order to assess the performance of the Firefly Algorithm and the Cuckoo Search Algorithm, they were compared with other well-known optimization techniques, such as Simulated Annealing and Local Search. Both meta-heuristics analysed in an in-depth computational study, reaching the conclusion that both techniques could be useful in Scheduling Problems and lead to satisfactory solutions quickly and efficiently. Moreover, the results of the analysis show that the Firefly Algorithm, despite having a high runtime, performs better than the other techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

Collaborative Planning in Non-Hierarchical Networks-An Intelligent Negotiation-Based Framework

Autores
Bastos, J; Azevedo, A; Avila, P; Mota, A; Costa, L; Castro, H;

Publicação
APPLIED SCIENCES-BASEL

Abstract
In today's competing business market, companies are constantly challenged to dynamically adapt to customer expectations by diminishing the time response that goes from the beginning of the business opportunity to the satisfaction of the customer need. Simultaneously, there is increased recognition of the advantages that companies obtain in focusing on their core business and seeking other competencies through partnerships with other partners by forming collaborative networks. These new collaborative organizational structures require a new set of methods and tools to support the management of manufacturing processes across the entire supply chain. The present paper addresses the collaborative production planning problem in networks of non-hierarchical, decentralized, and independent companies. By proposing a collaborative planning intelligent framework composed of a web-based set of methods, tools, and technologies, the present study intends to provide network stakeholders with the necessary means to responsively and efficiently address each one of the market business opportunities. Through this new holistic framework, the managers of the networked companies can address the challenges posed during collaborative network formation and supply chain production planning.

2023

Data Science for Industry 4.0 and Sustainability: A Survey and Analysis Based on Open Data

Autores
Castro, H; Costa, F; Ferreira, T; Avila, P; Cruz Cunha, M; Ferreira, L; Putnik, GD; Bastos, J;

Publicação
MACHINES

Abstract
In the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found.

Teses
supervisionadas

2023

Proposta De Modelo De Referência Para Gestão Multi-Projeto

Autor
CARLOTA PINTO MOREIRA

Instituição
IPP-ISEP

2023

CASO DE ESTUDO - MODELAÇÃO DE PROCESSOS, MELHORIA E MONITORAMENTO

Autor
MATEUS COELHO MARCHIORI

Instituição
IPP-ISEP

2022

MELHORIA DO PROCESSO DE GESTÃO DE INFORMAÇÃO NO SUPORTE AO CONTROLO DE QUALIDADE NUMA EMPRESA DO RAMO AUTOMÓVEL

Autor
TIAGO ANDRÉ MOURA OLIVEIRA

Instituição
IPP-ISEP

2022

Estudo Da Implementação De Um Sistema De Monitorização E Análise De Dados Na Indústria Metalomecânica

Autor
JOÃO MIGUEL SOARES CARNEIRO

Instituição
IPP-ISEP

2021

APLICAÇÃO LEAN MANUFACTURING NA REDUÇÃO DO TEMPO DE RESPOSTA NO SETOR DE ENERGIAS RENOVÁVEIS

Autor
TIAGO JESUS GONÇALVES

Instituição
IPP-ISEP