About Me

My name is João A. Duro and I am a Research Associate in the Department of Automatic Control and Systems Engineering at the University of Sheffield, UK.

I received a Licentiate degree in Engineering of Systems and Informatics from University of Algarve, Portugal, in 2007, and a PhD degree in Computer Science from the University of Cranfield, UK, 2013. Before joining the University of Sheffield in October 2015, I was an Interoperability Test Intern at Blackberry Limited (2007-2008), a Research Assistant at Sheffield Hallam University (2008-2009), and a Post-Doctoral Researcher at the University of Bath (2012-2015).

My research interests are in the design and application of metaheuristics, in particular evolutionary algorithms, for solving optimization problems. Topics that I am interested in are multi-objective optimization, multiple criteria decision-making, bi-level optimization, swarm intelligence, surrogate (Bayesian)-based optimization, multidisciplinary design optimization, and machine learning.

I am currently working on:

  1. collaborative multi-objective optimization for the design of complex systems;
  2. robust optimization of expensive uncertain multi-objective optimization problems;
  3. software engineering.

Papers

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  2023 (5)
A Scalable Test Suite for Bi-objective Multidisciplinary Optimization. Johnson, V.; Duro, J. A.; Kadirkamanathan, V.; and Purshouse, R. C. In Evolutionary Multi-Criterion Optimization, pages 319–332, 2023. Springer Nature Switzerland
A Scalable Test Suite for Bi-objective Multidisciplinary Optimization [link]Paper   doi   link   bibtex   2 downloads  
Methods for constrained optimization of expensive mixed-integer multi-objective problems, with application to an internal combustion engine design problem. Duro, J. A.; Ozturk, U. E.; Oara, D. C.; Salomon, S.; Lygoe, R. J.; Burke, R.; and Purshouse, R. C. European Journal of Operational Research, 307(1): 421–446. 2023.
Methods for constrained optimization of expensive mixed-integer multi-objective problems, with application to an internal combustion engine design problem [link]Paper   doi   link   bibtex  
Identifying Correlations in Understanding and Solving Many-Objective Optimisation Problems. Chugh, T.; Gaspar-Cunha, A.; Deutz, A. H.; Duro, J. A.; Oara, D. C.; and Rahat, A. In Brockhoff, D.; Emmerich, M.; Naujoks, B.; and Purshouse, R., editor(s), Many-Criteria Optimization and Decision Analysis: State-of-the-Art, Present Challenges, and Future Perspectives, pages 241–267. Springer International Publishing, Cham, 2023.
Identifying Correlations in Understanding and Solving Many-Objective Optimisation Problems [link]Paper   doi   link   bibtex  
A Distributed Multi-Disciplinary Design Optimization Benchmark Test Suite with Constraints and Multiple Conflicting Objectives. Johnson, V.; Duro, J.; Kadirkamanathan, V.; and Purshouse, R. In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, of GECCO '23 Companion, pages 1611-–1619, New York, NY, USA, 2023. Association for Computing Machinery
A Distributed Multi-Disciplinary Design Optimization Benchmark Test Suite with Constraints and Multiple Conflicting Objectives [link]Paper   doi   link   bibtex  
Can social norms explain long-term trends in alcohol use? Insights from inverse generative social science. Vu, T. M.; Buckley, C.; Duro, J. A; Brennan, A.; Epstein, J. M; and Purshouse, R. C Journal of Artificial Societies and Social Simulation, 26(2): 4. 2023.
Can social norms explain long-term trends in alcohol use? Insights from inverse generative social science [link]Paper   doi   link   bibtex  
  2022 (2)
Toward scalable benchmark problems for multi-objective multidisciplinary optimization. Johnson, V.; Duro, J. A.; Kadirkamanathan, V.; and Purshouse, R. C. In 2022 IEEE Symposium Series On Computational Intelligence (IEEE SSCI), pages 133–140, 2022. IEEE
Toward scalable benchmark problems for multi-objective multidisciplinary optimization [link]Paper   doi   link   bibtex  
Exploring social theory integration in agent-based modelling using multi-objective grammatical evolution. Vu, T. M.; Buckley, C.; Duro, J. A.; and Purshouse, R. C. In ICML 2022 Workshop AI for Agent-Based Modelling, 2022.
Exploring social theory integration in agent-based modelling using multi-objective grammatical evolution [link]Paper   link   bibtex  
  2021 (2)
Liger: A cross-platform open-source integrated optimization and decision-making environment. Duro, J. A.; Yan, Y.; Giagkiozis, I.; Giagkiozis, S.; Salomon, S.; Oara, D. C.; Sriwastava, A. K.; Morison, J.; Freeman, C. M.; Lygoe, R. J.; Purshouse, R. C.; and Fleming, P. J. Applied Soft Computing, 98: 106851. 2021.
Liger: A cross-platform open-source integrated optimization and decision-making environment [link]Paper   doi   link   bibtex  
Component-Based Design of Multi-Objective Evolutionary Algorithms Using the Tigon Optimization Library. Duro, J. A.; Oara, D. C.; Sriwastava, A. K.; Yan, Y.; Salomon, S.; and Purshouse, R. C. In Proceedings of the Genetic and Evolutionary Computation Conference, of GECCO ’21, New York, NY, USA, 2021. ACM
Component-Based Design of Multi-Objective Evolutionary Algorithms Using the Tigon Optimization Library [link]Paper   doi   link   bibtex  
  2019 (1)
sParEGO – A Hybrid Optimization Algorithm for Expensive Uncertain Multi-objective Optimization Problems. Duro, J. A.; Purshouse, R. C.; Salomon, S.; Oara, D. C.; Kadirkamanathan, V.; and Fleming, P. J. In Deb, K.; Goodman, E.; Coello Coello, C. A.; Klamroth, K.; Miettinen, K.; Mostaghim, S.; and Reed, P., editor(s), Evolutionary Multi-Criterion Optimization, pages 424–438, Cham, 2019. Springer International Publishing
sParEGO – A Hybrid Optimization Algorithm for Expensive Uncertain Multi-objective Optimization Problems [link]Paper   doi   link   bibtex  
  2018 (2)
Multi-objective optimization for distributed design of complex systems. Duro, J. A. In EURO 2018: 29th European Conference on Operational Research, Valencia, Spain, 2018. Steam: Multiobjective Optimization
link   bibtex  
Collaborative Multi-Objective Optimization for Distributed Design of Complex Products. Duro, J. A.; Yan, Y.; Purshouse, R. C.; and Fleming, P. J. In Proceedings of the Genetic and Evolutionary Computation Conference, of GECCO ’18, pages 625-–632, New York, NY, USA, 2018. ACM
Collaborative Multi-Objective Optimization for Distributed Design of Complex Products [link]Paper   doi   link   bibtex  
  2017 (1)
Timing the Decision Support for Real-World Many-Objective Optimization Problems. Duro, J. A.; and Saxena, D. K. In Trautmann, H.; Rudolph, G.; Klamroth, K.; Schütze, O.; Wiecek, M.; Jin, Y.; and Grimme, C., editor(s), Evolutionary Multi-Criterion Optimization, pages 191–205, Cham, 2017. Springer International Publishing
Timing the Decision Support for Real-World Many-Objective Optimization Problems [link]Paper   doi   link   bibtex  
  2016 (2)
Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms. Saxena, D. K.; Sinha, A.; Duro, J. A.; and Zhang, Q. IEEE Transactions on Evolutionary Computation, 20(4): 485–498. 2016.
Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms [link]Paper   doi   link   bibtex  
Multi-sensor data fusion framework for CNC machining monitoring. Duro, J. A.; Padget, J. A.; Bowen, C. R.; Kim, H. A.; and Nassehi, A. Mechanical Systems and Signal Processing, 66-67: 505–520. 2016.
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  2015 (1)
Topology Optimisation of Additively Manufactured Impact Resistant Structures. Kim, H. A.; Duro, J. A.; McShane, G. J.; and Theobald, P. S. In Proceedings of the 23rd UK Conference of the Association for Computational Mechanics in Engineering, pages 315–318, 2015.
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  2014 (1)
Machine learning based decision support for many-objective optimization problems. Duro, J. A.; Saxena, D. K.; Deb, K.; and Zhang, Q. Neurocomputing, 146: 30–47. 2014. Bridging Machine learning and Evolutionary Computation (BMLEC) Computational Collective Intelligence
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  2013 (2)
Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms. Saxena, D. K.; Duro, J. A.; Tiwari, A.; Deb, K.; and Zhang, Q. IEEE Transactions on Evolutionary Computation, 17(1): 77–99. 2013.
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Identifying the redundant, and ranking the critical, constraints in practical optimization problems. Saxena, D.; Rubino, A.; Duro, J. A.; and Tiwari, A. Engineering Optimization, 45(7): 787–809. 2013.
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  2011 (1)
Framework for Many-Objective Test Problems with Both Simple and Complicated Pareto-Set Shapes. Saxena, D. K.; Zhang, Q.; Duro, J. A.; and Tiwari, A. In Takahashi, R. H. C.; Deb, K.; Wanner, E. F.; and Greco, S., editor(s), Evolutionary Multi-Criterion Optimization, pages 197–211, Berlin, Heidelberg, 2011. Springer Berlin Heidelberg
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  2009 (1)
Robots team tasks in the GUARDIANS project. Basic and emerging behaviours. Alboul, L.; Duro, J. A.; Penders, J.; and Saez-Pons, J. In 14th Int. Symposium on Robotics Research (ISRR09), Lucerne, Switzerland, 2009.
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  2008 (1)
Particle swarm optimization applied to the chess game. Duro, J. A.; and de Oliveira , J. V. In 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pages 3702–3709, 2008.
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