The Fast and the Robust: Trade‐Offs Between Optimization Robustness and Cost in the Calibration of Environmental Models

[1]  P. Bayer,et al.  Evolutionary algorithms for the optimization of advective control of contaminated aquifer zones , 2004 .

[2]  Nicholas I. M. Gould,et al.  A Note on Performance Profiles for Benchmarking Software , 2016, ACM Trans. Math. Softw..

[3]  André da Motta Salles Barreto,et al.  Probabilistic performance profiles for the experimental evaluation of stochastic algorithms , 2010, GECCO '10.

[4]  Abdolreza Bahremand,et al.  Predictive Analysis and Simulation Uncertainty of a Distributed Hydrological Model , 2010 .

[5]  Aimo A. Törn,et al.  Stochastic Global Optimization: Problem Classes and Solution Techniques , 1999, J. Glob. Optim..

[6]  Y. D. Sergeyev,et al.  Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications) , 2000 .

[7]  S. Sorooshian,et al.  Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .

[8]  Pascal Côté,et al.  Comparison of Stochastic Optimization Algorithms in Hydrological Model Calibration , 2014 .

[9]  G. Seber,et al.  Nonlinear Regression: Seber/Nonlinear Regression , 2005 .

[10]  Zelda B. Zabinsky,et al.  Comparative Assessment of Algorithms and Software for Global Optimization , 2005, J. Glob. Optim..

[11]  Anne Auger,et al.  Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009 , 2010, GECCO '10.

[12]  Jorge J. Moré,et al.  Benchmarking optimization software with performance profiles , 2001, Math. Program..

[13]  Dmitri Kavetski,et al.  Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes , 2010 .

[14]  Bryan A. Tolson,et al.  Dynamically dimensioned search algorithm for computationally efficient watershed model calibration , 2007 .

[15]  Lino A. Costa,et al.  Benchmarking deterministic optimization algorithms using an outranking approach , 2016, Optim. Methods Softw..

[16]  George Kuczera,et al.  Comparison of Newton-type and SCE optimisation algorithms for the calibration of conceptual hydrological models , 2016 .

[17]  Theodor J. Stewart,et al.  Multiple Criteria Decision Analysis , 2001 .

[18]  Guoliang Xue,et al.  The MINPACK-2 test problem collection , 1992 .

[19]  László Pál,et al.  A Comparison of Global Search Algorithms for Continuous Black Box Optimization , 2012, Evolutionary Computation.

[20]  George Kuczera,et al.  Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors , 2017 .

[21]  John Doherty,et al.  Efficient accommodation of local minima in watershed model calibration , 2006 .

[22]  G. T. Timmer,et al.  Stochastic global optimization methods part I: Clustering methods , 1987, Math. Program..

[23]  Hermann Schichl,et al.  The optimization test environment , 2014 .

[24]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[25]  Bryan A. Tolson,et al.  A benchmarking framework for simulation-based optimization of environmental models , 2012, Environ. Model. Softw..

[26]  Anne Auger,et al.  Performance evaluation of an advanced local search evolutionary algorithm , 2005, 2005 IEEE Congress on Evolutionary Computation.

[27]  George Kuczera,et al.  Probabilistic optimization for conceptual rainfall-runoff models: A comparison of the shuffled complex evolution and simulated annealing algorithms , 1999 .

[28]  Lino A. Costa,et al.  Stochastic algorithms assessment using performance profiles , 2011, GECCO '11.

[29]  Reha Uzsoy,et al.  Experimental Evaluation of Heuristic Optimization Algorithms: A Tutorial , 2001, J. Heuristics.

[30]  Thomas Bäck,et al.  Empirical Investigation of Multiparent Recombination Operators in Evolution Strategies , 1997, Evolutionary Computation.

[31]  Dmitri Kavetski,et al.  Practical Use of Computationally Frugal Model Analysis Methods , 2016, Ground water.

[32]  Avi Ostfeld,et al.  Battle of the Water Networks II , 2014 .

[33]  Brian E. Skahill,et al.  More efficient PEST compatible model independent model calibration , 2009, Environ. Model. Softw..

[34]  D. Kavetski,et al.  Evaluating residual error approaches for post-processing monthly and seasonal streamflow forecasts , 2018 .

[35]  Subhash C. NarulaI,et al.  The Minimum Sum of Absolute Errors Regression: A State of the Art Survey , 1982 .

[36]  J. Doye,et al.  Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms , 1997, cond-mat/9803344.

[37]  John Doherty,et al.  Ground Water Model Calibration Using Pilot Points and Regularization , 2003, Ground water.

[38]  Eligius M. T. Hendrix,et al.  On Benchmarking Stochastic Global Optimization Algorithms , 2015, Informatica.

[39]  Charles Audet,et al.  Comparison of derivative-free optimization methods for groundwater supply and hydraulic capture community problems , 2008 .

[40]  Joseph H. A. Guillaume,et al.  Characterising performance of environmental models , 2013, Environ. Model. Softw..

[41]  Warren Hare,et al.  Best practices for comparing optimization algorithms , 2017, Optimization and Engineering.

[42]  Hans-Peter Kriegel,et al.  The (black) art of runtime evaluation: Are we comparing algorithms or implementations? , 2017, Knowledge and Information Systems.

[43]  Stefan M. Wild,et al.  Benchmarking Derivative-Free Optimization Algorithms , 2009, SIAM J. Optim..

[44]  Jasper A Vrugt,et al.  Improved evolutionary optimization from genetically adaptive multimethod search , 2007, Proceedings of the National Academy of Sciences.

[45]  Ernesto G. Birgin,et al.  2 . 2 Meaning of “ to solve a problem ” , 2011 .

[46]  Avi Ostfeld,et al.  Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions , 2014, Environ. Model. Softw..

[47]  Kalyanmoy Deb,et al.  Introducing Robustness in Multi-Objective Optimization , 2006, Evolutionary Computation.

[48]  Q. J. Wang.  The Genetic Algorithm and Its Application to Calibrating Conceptual Rainfall-Runoff Models , 1991 .