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Journals

  1. The Bi-Objective Critical Node Detection Problem
    M. Ventresca, K. Harrison and B. Ombuki-Berman
    European Journal of Operational Research (accepted), 2017.
  2. Action-based Modeling of Complex Networks
    V. Arora and M. Ventresca
    Nature Scientific Reports 7:6673, 2017.
  3. New Multi Objective Optimization Approach to Rehabilitate and Maintain Sewer Networks Based on Whole Life Cycle Behavior
    A. Altarabsheh, A. Kandil and M. Ventresca
    Journal of Computing in Civil Engineering (to appear), 2017.
  4. A Meta-Analysis of Centrality Measures for Comparing and Generating Complex Network Models
    K. Harrison, M. Ventresca and B. Ombuki-Berman
    Journal of Computational Science 17(1):205-215, 2016.
  5. Efficiently Identifying Critical Nodes in Large Complex Networks
    M. Ventresca and D. Aleman
    Computational Social Networks, 2(6):0.1186/s40649-015-0010-y, 2015.
  6. Network Robustness Versus Multi-Strategy Sequential Attack
    M. Ventresca and D. Aleman
    Journal of Complex Networks, 3(1):126-146, 2015.
  7. Antibody Landscapes after Influenza Virus Infection or Vaccination
    J.M. Fonville, S.H. Wilks, S.L. James, A. Fox, M. Ventresca, M. Aban, L. Xue, T.C. Jones, N.M.H. Le, Q.T. Pham, N.D. Tran, Y. Wong, A. Mosterin, L.C. Katzelnick, D. Labonte, T.T. Le, G. van der Net, E. Skepner, C.A. Russell, T.D. Kaplan, G.F. Rimmelzwaan, N. Masurel, J.C. de Jong, A. Palache, W.E.P. Beyer, Q.M. Le, T.H. Nguyen, H.F.L. Wertheim, A.C. Hurt, A.D.M.E. Osterhaus, I.G. Barr, R.A.M. Fouchier, P.W. Horby and D.J. Smith
    Science, 346(6212):996-1000, 2014.
  8. A Randomized Rounding Algorithm with Local Search for Containment of Pandemic Disease Spread
    M. Ventresca and D. Aleman
    Computers and Operations Research, 48:11-19, 2014.
  9. A Derandomized Approximation Algorithm for the Critical Node Detection Problem
    M. Ventresca and D. Aleman
    Computers and Operations Research, 43(3): 261-270, 2014.
  10. Genetic Programming for the Automatic Inference of Graph Models for Complex Networks
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    IEEE Transactions on Evolutionary Computation, 18(3):405-419, 2014.
  11. Evaluation of Strategies to Mitigate Contagion Spread Using Social Network Characteristics
    M. Ventresca and D. Aleman
    Social Networks, 35(1):75-88, 2013.
  12. The Polyfunctionality of Human Memory CD8+ T Cells Elicited by Acute and Chronic Virus Infections Is Not Influenced by Age
    A. Lelic, C. Verschoor, M. Ventresca, R. Parsons, C. Evelegh, D. Bowdish, M. R. Betts, M. B. Loeb and J. L. Bramson
    PLoS Pathogens, 8(12):e1003076, 2012.
  13. Global Search Algorithms Using a Combinatorial Unranking-Based Problem Representation for the Critical Node Detection Problem
    M. Ventresca
    Computers and Operations Research, 39(11):2763-2775, 2012. Problem Instances
  14. An Intuitive Distance-Based Explanation of Opposition-Based Sampling
    S. Rahnamayan, G. Wang and M. Ventresca
    Applied Soft Computing, 12(9):2828-2839, 2012.
  15. Enhancing Particle Swarm Optimization using Generalized Opposition-Based Learning
    H. Wang, Z. Wu, S. Rahnamayan, Y. Liu and M. Ventresca
    Information Sciences, 181(20):4699-4714, 2011.
  16. Prevalence of Antibodies Against Seasonal Influenza A and B Viruses in Children in The Netherlands
    R. Bodewes, G. de Mutsert, F. van der Klis, M. Ventresca, S. Wilks, D. Smith, M. koopmans, R. A. M. Fouchier, A. D. M. E. Osterhaus, G. F. Rimmelzwaan
    Clinical and Vaccine Immunology, 18(3):469-476, 2011.
  17. A Note on Opposition Versus Randomness in Soft Computing Techniques
    M. Ventresca, S. Rahnamayan and H. R. Tizhoosh
    Applied Soft Computing, 10(3):956-967, 2010.
  18. A Diversity Maintaining Population-Based Incremental Learning Algorithm
    M. Ventresca and H. R. Tizhoosh
    Information Sciences, 178(21):4038-4056, 2008.
  19. A Memetic Algorithm for Performing Memory Assignment in Dual-Bank DSPs
    G. Grewal, S. Coros and M. Ventresca
    Computational Intelligence and Applications, 6(4):473-497, 2006.
  20. A Genetic Algorithm for the Design of Two Connected Networks with Bounded Rings
    M. Ventresca and B. Ombuki
    Computational Intelligence and Applications, 5(2):267-281, 2005.
  21. Local Search Genetic Algorithm for the Job Shop Scheduling Problem
    B. Ombuki and M. Ventresca
    Applied Intelligence, 21(1):99-109, 2004.

Refereed Conference Proceedings

  1. TrACA: Using Ant Colony Metaheuristic for the Winner Determination Problem
    A. Ray, M. Ventresca and K. Kannan
    The Workshop on Information Technologies and Systems, (accepted), Seoul, South Korea, 2017.
  2. Action-based Model for Topologically Resilient Supply Networks
    V. Arora and M. Ventresca
    The 6th International Conference on Complex Networks and Their Applications, (accepted), Lyon, France, 2017.
  3. Attacking Unexplored Networks - the Probe-and-Attack Problem
    B. Chong and M. Ventresca
    The 6th International Conference on Complex Networks and Their Applications, (accepted), Lyon, France, 2017.
  4. Dynamic Generative Model of the Human Brain in Resting-state
    D. Guo, V. Arora, E. Amico, J. Goni and M. Ventresca
    The 6th International Conference on Complex Networks and Their Applications, (accepted), Lyon, France, 2017.
  5. The Inverse Problem of Discovering Complex Network Generators
    V. Arora and M. Ventresca
    International Conference on Inverse Problems in Engineering, 2017.
  6. A Multi-objective Optimization Approach for Generating Complex Networks
    V. Arora and M. Ventresca
    Genetic and Evolutionary Computation Conference, Companion pp:15-16, (GECCO) Denver, USA, 2016.
  7. Investigating Fitness Measures for the Automatic Construction of Graph Models
    K. Harrison, M. Ventresca and B. Ombuki-Berman
    Lecture Notes in Computer Science, 9028 pp:189-200, (Evo*) Copenhagen, Denmark, 2015.
  8. An Experimental Evaluation of Multi-Objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks
    M. Ventresca, K. Harrison and B. Ombuki-Berman
    Lecture Notes in Computer Science, 9028 pp:164-176, (Evo*) Copenhagen, Denmark, 2015.
  9. A Fast Greedy Algorithm for the Critical Node Detection Problem
    M. Ventresca and D. Aleman
    Workshop on Computational Social Networks/COCOA, Maui, USA, 2014.
  10. A Region Growing Algorithm for Detecting Critical Nodes
    M. Ventresca and D. Aleman
    Workshop on Computational Social Networks/COCOA, Maui, USA, 2014.
  11. Deriving Public Policies from Contact Networks
    M. Ventresca and D. Aleman
    8th INFORMS Workshop on Data Mining and Health Informatics, Minneapolis, USA, 2013.
  12. Automatic Inference of Hierarchical Graph Models using Genetic Programming with an Application to Cortical Networks
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    Genetic and Evolutionary Computation Conference (GECCO), pp:893-900, Amsterdam, Netherlands, 2013.
  13. Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures
    M. Ventresca, A. Runka and B. Ombuki-Berman
    13th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), pp:214-225, Vienna, Austria, 2013.
  14. Automatic Generation of Graph Models For Complex Networks by Genetic Programming
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    Genetic and Evolutionary Computation Conference (GECCO), pp: 711-718, Philadelphia, USA, 2012.
  15. A Search Space Analysis for the Waste Collection Vehicle Routing Problem with Time Windows
    A. Runka, B. Ombuki-Berman and M. Ventresca
    Genetic and Evolutionary Computation Conference (GECCO), pp:1813-1814, Montreal, Canada, 2009.
  16. Improving Gradient-Based Learning Algorithms for Large Scale Neural Networks
    M. Ventresca and H. R. Tizhoosh
    IEEE International Joint Conference on Neural Networks, pp:1529-1536, Atlanta, USA, 2009.
  17. Numerical Condition of Feedforward Networks with Opposite Transfer Functions
    M. Ventresca and H. R. Tizhoosh
    IEEE International Joint Conference on Neural Networks (IJCNN), pp:3232-3239, Hong Kong, China, 2008.
  18. Simulated Annealing with Opposite Neighbors
    M. Ventresca and H. R. Tizhoosh
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:186-192, Honolulu, USA, 2007.
  19. Opposite Transfer Functions and Backpropagation Through Time
    M. Ventresca and H. R. Tizhoosh
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:570-577, Honolulu, USA, 2007.
  20. Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers
    M. Ventresca and B. Ombuki-Berman
    IEEE Symposium on Artificial Life (CI-ALIFE), pp:77-84, Honolulu, USA, 2007.
  21. Search Difficulty of Two-Connected Ring-based Topological Network Designs
    B. Ombuki-Berman and M. Ventresca
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:267-274, Honolulu, USA, 2007.
  22. Improving the Convergence of Backpropagation by Opposite Transfer Functions
    M. Ventresca, H. R. Tizhoosh
    International Joint Conference on Neural Networks (IJCNN), pp:9527-9534, Vancouver, Canada, 2006.
  23. Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks
    M. Ventresca and B. Ombuki
    International Joint Conference on Neural Networks (IJCNN), pp:8947-8954, Vancouver, Canada, 2006.
  24. Optimized Memory Assignment for DSPs
    G. Grewal, S. Coros, D. Banerji, A. Morton and M. Ventresca
    Congress on Evolutionary Computation (CEC), pp:371-379, Vancouver, Canada, 2006.
  25. Ant Colony Optimization for Job Shop Scheduling Problem
    M. Ventresca and B. Ombuki
    8th International Conference On Artificial Intelligence and Soft Computing (ASC 2004), CDROM:451-152. Marbella, Spain, 2004.
  26. A Genetic Algorithm for the Design of Two Connected Networks with Bounded Rings
    M. Ventresca and B. Ombuki
    8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), Birmingham, UK, 2004.
  27. Meta-heuristics for the Job Shop Scheduling Problem
    M. Ventresca and B. Ombuki
    Proceedings of Late Breaking Papers, Genetic and Evolutionary Computation Conference(GECCO) pp:303-306, Chicago, USA, 2003.

Magazine Articles

  1. Mining Social Contact Networks for Pandemic Disease Mitigation Strategies
    M. Ventresca and D. Aleman
    OR/MS Today, 41(2):pp:26-30, 2014.

Books

  1. Oppositional Concepts in Computational Intelligence
    H. R. Tizhoosh and M. Ventresca (Eds.),
    Studies in Computational Intelligence, Springer-Verlag, 2008.

Book Chapters

  1. Deriving Pandemic Disease Mitigation Strategies by Mining Social Contact Networks
    M. Ventresca, A. Szatan, B. Say and D. Aleman
    Optimization, Control, and Applications in the Information Age, Springer Proceedings of Mathematics and Statistics, 130(359-381),2015.
  2. Approximation Algorithms for Detecting Critical Nodes
    M. Ventresca and D. Aleman
    NATO Science for Peace and Security Series -D: Information and Communication Security, IOS Press, pp:289-305, 2014.
  3. The Use of Opposition for Decreasing Function Evaluations in Population-Based Search
    M. Ventresca, S. Rahnamayan and H. R. Tizhoosh
    Computational Intelligence in Optimization-Applications and Implementations, Springer-Verlag, 2010.
  4. Two Frameworks for Improving Gradient-Based Learning Algorithms
    M. Ventresca and H. R. Tizhoosh
    Oppositional Concepts in Computational Intellligence, 2008.
  5. Opposition-Based Computing
    H. R. Tizhoosh, M. Ventresca and S. Rahnamayan
    Oppositional Concepts in Computational Intellligence, 2008.

Refereed and Invited Abstracts

  1. Modeling diffusion processes in the brain through a cooperative learning ant colony-inspired algorithm
    U. Tipnis, E. Amico, M. Ventresca and J. Goni
    5th Indiana Neuroimaging Symposium and Hackathon on Brain Connectomics, Lafayette, USA, 2017.
  2. TrACA: Using Ant Colony Metaheuristics to solve the Winner Determination Problem
    A. Ray, M. Ventresca and K. Kannan
    INFORMS Annual Meeting, Houston, USA, 2017.
  3. Automated Modeling and Design of Complex Networks
    V. Arora and M. Ventresca
    International School and Conference on Network Science, Indianapolis, USA, 2017.
  4. Modeling Diffusion Processes in the Brain through a Cooperative Learning Ant Colony-Inspired Algorithm
    U. Tipnis, E. Amico, M. Ventresca and J. Goni
    International School and Conference on Network Science, Indianapolis, USA, 2017.
  5. Action-based Network Models
    V. Arora and M. Ventresca
    INFORMS, Philadelphia, USA, 2015.
  6. Automatically Inferring Complex Network Models
    M. Ventresca
    INFORMS Annual Meeting, Philadelphia, USA, 2015.
  7. Response surface optimization of pandemic policies
    A. Szatan, B. Say, M. Ventresca, D. M. Aleman
    IIE Annual Conference, Nashville, USA, 2015.
  8. A parallelized framework for network-based phenomenon spread with application to pandemic simulation
    Y. L. de Oliveira, D. M. Aleman, M. Ventresca
    IIE Annual Conference, Nashville, USA, 2015.
  9. Experimental Evaluation of Network Robustness against Multi-Strategy Greedy Attacks
    M. Ventresca and D. Aleman
    INFORMS, San Francisco, USA, 2014.
  10. Rule Mining in Critical Node Detection
    M. Ventresca and D. Aleman
    IFORS, Barcelona, Spain, 2014.
  11. Application of Response Surfaces to Pandemic Outbreak Mitigation Strategy Optimization
    B. Say, M. Ventresca and D. Aleman
    ISERC, Montreal, Canada, 2014.
  12. Effect of Peer Influence on Pandemic Disease Spread
    K. Chan, M. Ventresca and D. Aleman
    ISERC, Montreal Canada, 2014.
  13. Automatically Generating Public Policies from Contact Networks
    M. Ventresca and D. Aleman
    INFORMS Annual Meeting, Minneapolis USA, 2013.
  14. A Critical Node Detection Approach to Pandemic Planning
    M. Ventresca and D. Aleman
    55th Canadian Operational Research Society Annual Conference, Vancouver, Canada, 2013.
  15. Infectious Disease Mitigation: From Contact Networks to Public Policies
    M. Ventresca and D. Aleman
    INFORMS Healthcare, Chicago, USA, 2013.
  16. Using a Pandemic Disease Spread Simulation Model to Make Deterministic, Graph-Theory Based Vaccine Decisions
    M. Ventresca and D. Aleman
    IIE Industrial and Systems Engineering Research Conference, San Juan, Puerto Rico, 2013.
  17. The polyfunctionality of memory CD8+ T cells in response to chronic and acute viral infections is not influenced by age
    A. Lelic, M. Ventresca, C. Verschoor, R. Parsons, C. Evelegh, D. Bowdish, M. Betts,M. Loeb, and J. Bramson
    The Journal of Immunology (conference abstract), 188(1):105.49, 2012.
  18. Evaluation of Disease Mitigation Strategies Using Social Network Characteristics
    M. Ventresca and D. Aleman
    INFORMS Annual Meeting, Phoenix, USA, 2012.
  19. Simplifying the Interpretation of Human Serology in Vaccine Selection
    S.L. James, J.M. Fonville, M. Ventresca, L. Xue, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E.P. Beyer, F. Pistoor, A. Palache, A. Hurt, I.G. Barr, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    Public Health Science, Royal Society of Medicine, UK, 2012.
  20. Antibody Landscapes: Quantifying the Antibody Immune Response
    J.M. Fonville, S. L. James, M. Ventresca, L. Xue, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E. Beyer, F. Pistoor, A. Palache, A. Hurt, I.G. Barr, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    6th Orthomyxovirus Research Conference, Montreal, Canada, 2012.
  21. Controlling for Antigenic Differences Simplifies the Interpretation of Human Serology Data
    S. L. James, M. Ventresca, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E. Beyer, F. Pistoor, A. Palache, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    The Fourth ESWI Influenza Conference, Malta, 2011.