Miguel Vieira

Miguel Vieira


Miguel Vieira obtained in 2017 his PhD in Leaders for Technical Industries (Engineering Design and Advanced Manufacturing focus area) by the Instituto Superior Técnico in partnership with the Massachusetts Institute of Technology under the MIT Portugal Program. Currently he is an Assistant Professor at the Faculty of Engineering at Lusófona University, Lisbon and Researcher at RCM2+. His main topics of research expertise have been centered in the industrial engineering challenges of applied optimization methods and simulation models to solve supply chain, design, production planning and scheduling problems of complex manufacturing systems. In particular, the main research is focused at developing mathematical programming models (LP, IP, MILP and MINLP), decomposition methods and non-exact approaches to provide optimal solutions to industrial cases, considering both deterministic and stochastic scenarios, with several first-author publications. Current research projects include the risk assessment of process design and planning, dynamic scheduling strategies for decisional tools in the context of Industry 4.0 paradigm and methods for improving solutions of real-world industrial optimization problems. Particular relevance has been given to the efficient use of novel automation technologies in industrial processes, with the development of machine learning algorithms based in deep and reinforcement learning for novel interfaces for human-robot interaction/cooperation in industrial processes and its integration on the decision-support operations to increase flexibility and productivity of production systems. Miguel Vieira is a Visiting Researcher in Instituto Superior Técnico Centro de Estudos de Gestão and Visiting Researcher in Universidade de Coimbra Centro de Engenharia Mecânica Materiais e Processos. Published 8 articles in journals. Has 11 section(s) of books. Organized 7 event(s). Participated in 2 event(s). Supervised 3 MSc dissertation(s). Has received 6 awards and/or honors. Participates and/or participated as Other in 2 project(s), Post-doc Fellow in 1 project(s) and Researcher in 3 project(s). Works in the area(s) of Social Sciences with emphasis on Economics and Business with emphasis on Industrial Relations, Exact Sciences with emphasis on Computer and Information Sciences, Engineering and Technology with emphasis on Other Engineering and Technologies and Engineering and Technology with emphasis on Chemical Engineering. In their professional activities interacted with 53 collaborator(s) co-authorship of scientific papers. In his curriculum Ciência Vitae the most frequent terms in the context of scientific, technological and artistic-cultural output are: Multipurpose batch plants; Risk assessment; Conditional value-at-risk; Stochastic programming; Augmented e-constraint method; Programação matemática; Otimização; Gestão de Operações e de Cadeias de Abastecimento; Análise de Decisão e de Risco; Avaliação Ambiental e da Sustentabilidade; Empreendedorismo e Inovação; Conditional Value at Risk (CVaR); Effective risk metric; Stochastic parameters; .


  • Doutoramento
    Líderes para as Indústrias Tecnológicas
  • Mestrado integrado
    Engenharia Química
  • Especialização pós-licenciatura
    Technology Management Enterprise


Journal article

  • 2024-02-08, An Exact Approach to the Multi-Compartment Vehicle Routing Problem: The Case of a Fuel Distribution Company, Mathematics
  • 2022-06-06, Design and Operation of Multipurpose Production Facilities Using Solar Energy Sources for Heat Integration Sustainable Strategies, Mathematics
  • 2022-05-03, A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line, International Journal of Production Research
  • 2021-04, A study on a Q-Learning algorithm application to a manufacturing assembly problem, Journal of Manufacturing Systems
  • 2020-08-17, Assessment of financial risk in the design and scheduling of multipurpose plants under demand uncertainty, International Journal of Production Research
  • 2019-03, A model-based decision support framework for the optimisation of production planning in the biopharmaceutical industry, Computers & Industrial Engineering
  • 2017-12, Production and maintenance planning optimisation in biopharmaceutical processes under performance decay using a continuous-time formulation: A multi-objective approach, Computers & Chemical Engineering
  • 2016-08, Optimal planning and campaign scheduling of biopharmaceutical processes using a continuous-time formulation, Computers & Chemical Engineering

Thesis / Dissertation

  • 2017, PhD, Towards the development of a decision-support tool for the production planning and campaign scheduling of biopharmaceutical facilities

Book chapter

  • 2024, The Consistent Vehicle Routing Problem: An Application to the Pharmaceutical Supply Chain
  • 2023, An Approach to the Design of Resilient Biomass Supply Chain Using Discrete Event Simulation
  • 2023, A Discrete-Event Simulation Approach to the Design and Planning of Biomass Supply Chains considering Technological Learning, Elsevier
  • 2022, Assessment of biomass supply chain design and planning using discrete-event simulation modeling, Elsevier
  • 2021, Towards an integrated decision-support framework for the new generation of manufacturing systems
  • 2019, Integrating Simulation and Optimization for Process Planning and Scheduling Problems, 29th European Symposium on Computer Aided Process Engineering, 46, Elsevier
  • 2018, Risk assessment for the design and scheduling optimization of periodic multipurpose batch plants under demand uncertainty, 28th European Symposium on Computer Aided Process Engineering, 43, Elsevier
  • 2016, Optimisation of Maintenance Planning into the Production of Biopharmaceuticals with Performance Decay using a Continuous-time Formulation, 26th European Symposium on Computer Aided Process Engineering, 38, Elsevier
  • 2015, Planning and Scheduling in the Biopharmaceutical Industry: An Overview, Synthesis, Design, and Resource Optimization in Batch Chemical Plants, CRC Press
  • 2015, Periodic Versus Non-periodic Multipurpose Batch Plant Scheduling: A Paint Industry Case Study, CIM Series in Mathematical Sciences, Springer International Publishing
  • 2014, Optimal scheduling of multi-stage multi-product biopharmaceutical processes using a continuoustime formulation, 33

Conference paper

  • Conditional Value at Risk (CVaR) as a risk measure to support industrial plant design and scheduling decisions under demand uncertainty
  • A multi-objective approach on the optimal production and maintenance planning of biopharmaceutical processes under performance decay using a continuous-time formulation, Foundations of Computer Aided Process Operations / Chemical Process Control
  • 2018, Simulation-optimization approach for the decision-support on the planning and scheduling of automated assembly lines

Conference abstract

  • 2019, Design and scheduling of multipurpose plants under demand uncertainty: A model-based decision support system, IO2019 XX Congresso APDIO
  • 2019, A Multi-objective Metaheuristic Approach for the Planning in Flexible Assembly Lines, IO2019 XX Congresso APDIO
  • 2018-06, A hybrid optimization-simulation solution for the planning and scheduling of automated assembly lines, IO2018 XVIII APDIO Conference
  • 2018, Escalonamento de linhas de produção flexíveis com utilização de Robots, IO2018 XIX Congresso APDIO
  • 2017, Simulation-Optimization framework for planning reconfigurable assembly lines, Computers and Industrial Engineering-CIE47
  • 2017, A decision-support framework for the planning optimisation of biopharmaceutical industrial processes, IO2017-XVIII Congresso APDIO
  • 2015, Unit-specific continuous time formulation for the scheduling of biopharmaceutical batch and continuous processes, Process Systems Engineering/ European Symposium on Computer Aided Process Engineering-PSE2015/ESCAPE25

Conference poster

  • 2022-11-06, Data-driven job-shop scheduling: the case of a metal packaging manufacturer, IO2022 - XXII Congress of the Portuguese Operational Research Association (APDIO), University of Évora.

Research technique

  • ICOMPASS – Development of a proof-of-concept prototype of a model-based decision-support tool for the production and maintenance planning optimization for biopharmaceutical industrial cases.


Lisboa 2020 Portugal 2020 Small financiado eu 2024 prr 2024 republica portuguesa 2024 Logo UE Financed Provedor do Estudante Livro de reclamaões Elogios