A benchmarking framework for simulation-based optimization of environmental models

Environmental Modelling and Software

Volumn 35, Issue , 2012, Pages 19-30

  Matott, L Shawn ^a   Tolson, Bryan A ^b   Asadzadeh, Masoud ^b  

^a UNIVERSITY AT BUFFALO   (United States)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Benchmark problems; Dynamically dimensioned search; Model pre emption; Particle swarm optimization; Simulation based optimization; Sorptive barrier design

Indexed keywords

ALTERNATIVE ALGORITHMS; BARRIER DESIGN; BENCH-MARK PROBLEMS; COMPUTATIONAL EXPENSE; COMPUTATIONAL SAVINGS; COST VALUES; DECISION VARIABLES; DYNAMICALLY DIMENSIONED SEARCH; ENVIRONMENTAL MODEL; ENVIRONMENTAL SYSTEMS; HAZARDOUS WASTES; LANDFILL LINER; LEAST-COST SOLUTIONS; NON-TRIVIAL; OPTIMAL DESIGN; OPTIMIZATION ALGORITHMS; PARTICLE SWARM OPTIMIZERS; SIMULATION MODEL; SIMULATION-BASED OPTIMIZATIONS; SOLUTION APPROACH; SYSTEM CONSTRAINTS;

ALGORITHMS; COMPUTER SIMULATION;

PARTICLE SWARM OPTIMIZATION (PSO);

ALGORITHM; BENCHMARKING; COST-BENEFIT ANALYSIS; ENVIRONMENTAL MANAGEMENT; ENVIRONMENTAL MODELING; GUIDELINE; HAZARDOUS WASTE; LANDFILL; LINER; NUMERICAL MODEL; OPTIMIZATION;

EID: 84860151277     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.02.002     Document Type: Article

References (71)

1. Adams B.J., Karney B.W., Cormier C.J., Lai A. Artesian landfill liner system: optimization and numerical analysis. Journal of Water Resources Planning and Management 1998, 124(6):345-356.
2. Ali M.M., Torn A., Viitanen S. A numerical comparison of some modified controlled random Search Algorithms. Journal of Global Optimization 1997, 11(4):377-385.
3. Barr R., Golden B., Kelly J., Resende M., Stewart W. Designing and reporting on computational experiments with heuristic methods. Journal of Heuristics 1995, 1(1):9-32.
4. Bartelt-Hunt S.L., Smith J.A., Burns S.E., Rabideau A.R. Evaluation of granular activated carbon, shale and two organoclays for use as sorptive amendments in clay landfill liners. Journal of Geotechnical and Geoenvironmental Engineering 2005, 131(7):848-856.
5. Bartelt-Hunt S.L., Culver T.B., Smith J.A., Matott L.S., Rabideau A.J. Optimal design of a compacted soil liner containing sorptive amendments. Journal of Environmental Engineering 2006, 132(7):769-776.
6. Baú D.A., Mayer A.S. Optimal design of pump-and-treat systems under uncertain hydraulic conductivity and plume distribution. Journal of Contaminant Hydrology 2008, 100(1-2):30-46.
7. Bayer P., Finkel M. Evolutionary algorithms for the optimization of advective control of contaminated aquifer zones. Water Resources Research 2004, 40(W06506). 19 pp.
8. Beielstein T., Parsopoulos K.E., Vrahatis M.N. Tuning PSO parameters through sensitivity analysis 2002, Technical Report, Reihe Computational Intelligence CI 124/02, Collaborative Research Center, Department of Computer Science, University of Dortmund, Available online at: http://ls11-www.cs.uni-dortmund.de/people/tom/.
9. Burn D.H., Yulianti J.S. Waste-load allocation using genetic algorithms. Journal of Water Resources Planning and Management 2001, 127(2):121-129.
10. Carroll R.W.H., Pohll G.M., Hershey R.L. An unconfined groundwater model of the Death Valley Regional Flow System and a comparison to its confined predecessor. Journal of Hydrology 2009, 373(3-4):316-328.
11. Collette Y., Siarry P. Multiobjective Optimization: Principles and Case Studies 2003, Springer, Berlin, Germany.
12. Cools J., Broekx S., Vandenberghe V., Sels H., Meynaerts E., Vercaemst P., Seuntjens P., Van Hulle S., Wustenberghs H., Bauwens W., Huygens M. Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen. Environmental Modelling & Software 2011, 26(1):44-51.
13. Deb K. An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering 2000, 186(2-4):311-338.
14. Draper A.J., Jenkins M.W., Kirby K.W., Lund J.R., Howitt R.E. Economic-engineering optimization for California water management. Journal of Water Resources Planning and Management 2003, 129(3):155-164.
15. Duan Q., Sorooshian S., Gupta V.K. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research 1992, 28(4):1015-1031.
16. Erickson M., Mayer A., Horn J. Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA). Advances in Water Resources 2002, 25(1):51-65.
17. Finsterle S., Zhang Y. Solving iTOUGH2 simulation and optimization problems using the PEST protocol. Environmental Modelling & Software 2011, 26(7):959-968.
18. Finsterle S. Demonstration of optimization techniques for groundwater plume remediation using iTOUGH2. Environmental Modelling & Software 2006, 21(5):665-680.
19. Foose G.J., Benson C.H., Edil T.B. Comparison of solute transport in three composite liners. Journal of Geotechnical and Geoenvironmental Engineering 2002, 128(5):391-403.
20. Fowler K.R., Reese J.P., Kees C.E., Dennis J.E., Kelley C.T., Miller C.T., Audet C., Booker A.J., Couture G., Darwin R.W., Farthing M.W., Finkel D.E., Gablonsky J.M., Gray G., Kolda T.G. Comparison of derivative-free optimization methods for groundwater supply and hydraulic capture community problems. Advances in Water Resources 2008, 31(5):743-757.
21. Franz K.J., Hogue T.S., Sorooshian S. Operational snow modeling: addressing the challenges of an energy balance model for National Weather Service forecasts. Journal of Hydrology 2008, 360(1-4):48-66.
22. Freeze R.A., Gorelick S.M. Convergence of stochastic optimization and decision analysis in the engineering design of aquifer remediation. Ground Water 1999, 37(6):934-954.
23. García S., Molina D., Lozano M., Herrera F. A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 special session on real parameter optimization. Journal of Heuristics 2009, 15:617-644.
24. Gibbons J.D., Chakraborti S. Nonparametric Statistical Inference 1992, Marcel Dekker, Inc., New York. third ed.
25. Gill M.K., Kaheil Y.H., Khalil A., Mckee M., Bastidas L. Multiobjective particle swarm optimization for parameter estimation in hydrology. Water Resources Research 2006, 42(7):W07417. doi:07410.01029/02005WR004528.
26. Gitau M.W., Veith T.L., Gburek W.J., Jarrett A.R. Watershed level best management practice selection and Placement in the Town Brook watershed, New York. Journal of the American Water Resources Association 2006, 42(6):1565-1581.
27. Goodman L.A. Kolmogorov-Smirnov test for psychological research. Psychologicul Bulletin 1954, 51:160-168.
28. Guan J., Aral M.M. Optimal design of groundwater remediation systems using fuzzy set theory. Water Resources Research 2004, 40(1):W01518. doi:01510.01029/02003WR002121.
29. Gullick R.W., Weber W.J. Evaluation of shale and organoclays as sorbent additives for low-permeability soil containment barriers. Environmental Science & Technology 2001, 35(7):1523-1530.
30. Hadka, D., Reed, P., in press. Diagnostic Assessment of Search Controls and Failure Modes in Many-Objective Evolutionary Optimization. Evolutionary Computation, doi:10.1162/EVCO_a_00053.
31. Herrera F., Lozano M., Molina D. Test Suite for the Special Issue of Soft Computing on Scalability of Evolutionary Algorithms and Other Metaheuristics for Large Scale Continuous Optimization Problems 2010, Available from:, University of Granada, Granada, Spain, 12 p. http://sci2s.ugr.es/eamhco/updated-functions1-19.pdf.
32. Hilton A.B.C., Culver T.B. Constraint handling for genetic algorithms in optimal remediation design. Journal of Water Resources Planning and Management 2000, 126(3):128-137.
33. Jia Y., Culver T.B. Robust optimization for total maximum daily load allocations. Water Resources Research 2006, 42(2):W02412.
34. Joslin D., Dragovich J., Hoa V., Terada J. Opportunistic fitness evaluation in a genetic algorithm for civil engineering design optimization. Proceedings of the 2006 IEEE Congress on Evolutionary Computation: Vancouver, BC, Canada 2006, 2904-2911.
35. Kalwij I.M., Peralta R.C. Simulation/optimization modeling for robust pumping strategy design. Ground Water 2006, 44(4):574-582.
36. Kennedy J., Eberhart R.C. Particle Swarm Optimization 1995, Proceedings of the IEEE International Conference on Neural Networks, Piscataway, NJ, 1942-1948 pp.
37. ® and organo-clay. Water Science and Technology 1996, 34(7-8):421-427.
38. Matott L.S., Rabideau A.J. NIGHTHAWK-A program for modeling saturated batch and column experiments incorporating equilibrium and kinetic biogeochemistry. Computers & Geosciences 2010, 36(2):253-256.
39. Matott L.S., Bartelt-Hunt S.L., Rabideau A.J., Fowler K.R. Application of heuristic optimization techniques and algorithm tuning to multi-layered sorptive barrier design. Environmental Science & Technology 2006, 40(20):6354-6360.
40. Mayer A.S., Kelley C.T., Miller C.T. Optimal design for problems involving flow and transport phenomena in saturated subsurface systems. Advances in Water Resources 2002, 25(8-12):1233-1256.
41. Medellín-Azuara J., Mendoza-Espinosa L.G., Lund J.R., Ramírez-Acosta R.J. The application of economic-engineering optimization for water management in Ensenada, Baja California, Mexico. Water Science & Technology 2007, 55(1-2):339-347.
42. Moré J.J., Wild S.M. Benchmarking derivative-free optimization algorithms. SIAM Journal on Optimization 2009, 20(1):172-191.
43. Muleta M.K., Nicklow J.W. Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model. Journal of Hydrology 2005, 306:127-145.
44. Nicklow J., Reed P., Savic D., Dessalegne T., Harrell L., Chan-Hilton A., Karamouz M., Minsker B., Ostfeld A., Singh A., Zechman E. State of the art for genetic algorithms and beyond in water resources planning and management. Journal of Water Resources Planning and Management 2010, 136(4):412-432.
45. Noether G. Note on the kolmogorov statistic in the discrete case. Metrika 1963, 7(1):115-116.
46. Painter B.D.M., Milke M.W. Comparison of factorial and scenario analysis methods for assessing uncertainty in the design of permeable reactive barriers. Ground Water Monitoring & Remediation 2007, 27(3):102-110.
47. Painter B.D.M. Optimization of Permeable Reactive Barriers for the Remediation of Contaminated Groundwater, Natural Resource Engineering Department 2005, Lincoln University, Canterbury, New Zealand.
48. Parno M.D., Fowler K.R., Hemker T. Framework for Particle Swarm Optimization with Surrogate Functions 2009, Darmstadt Technical University, Darmstadt, Germany, 11 p.
49. Peña-Haro S., Pulido-Velazquez M., Llopis-Albert C. Stochastic hydro-economic modeling for optimal management of agricultural groundwater nitrate pollution under hydraulic conductivity uncertainty. Environmental Modelling & Software 2011, 26(8):999-1008.
50. Rabideau A.J. MOUSER Version 1 User's Manual 2003, Available from, University at Buffalo, Department of Civil, Structural, and Environmental Engineering, Buffalo, NY: http://www.groundwater.buffalo.edu.
51. Rardin R.L., Uzsoy R. Experimental evaluation of heuristic optimization algorithms: a tutorial. Journal of Heuristics 2001, 7:261-304.
52. Razavi S., Tolson B.A., Matott L.S., Thomson N.R., MacLean A., Seglenieks F.R. Reducing the computational cost of automatic calibration through model preemption. Water Resources Research 2010, 46(11):W11523.
53. Regis R.G., Shoemaker C.A. Improved strategies for Radial basis function methods for global optimization. Journal of Global Optimization 2007, 37(1):113-135.
54. Rehana S., Mujumdar P.P. An imprecise fuzzy risk approach for water quality management of a river system. Journal of Environmental Management 2009, 90(11):3653-3664.
55. Schaake J., Duan Q., Andréassian V., Franks S., Hall A., Leavesley G. The model parameter estimation experiment (MOPEX). Journal of Hydrology 2006, 320(1-2):1-2.
56. Slaughter C.W., Marks D., Flerchinger G.N., Vactor S.S.V., Burgess M. Thirty-five years of research data collection at the Reynolds Creek experimental watershed, Idaho, United States. Water Resources Research 2001, 37(11):2819-2823.
57. Taillard E.D., Waelti P., Zuber J. Few statistical tests for proportions comparisons. European Journal of Operational Research 2008, 185(3):1336-1350.
58. Tang Y., Reed P., Wagener T. How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?. Hydrology and Earth System Sciences 2006, 10(2):289-307.
59. Tang Y., Reed P.M., Kollat J.B. Parallelization strategies for rapid and robust evolutionary multiobjective optimization in water resources applications. Advances in Water Resources 2007, 30(3):335-353.
60. Tolson B.A., Shoemaker C.A. Dynamically dimensioned search algorithm for computationally efficient watershed model calibration. Water Resources Research 2007, 43(W01413).
61. Tolson B.A., Asadzadeh M., Maier H.R., Zecchin A. Hybrid discrete dynamically dimensioned search (HD-DDS) algorithm for water distribution system design optimization. Water Resources Research 2009, 45(W12416).
62. Vasan A., Simonovic S.P. Optimization of water distribution network design using differential evolution. Journal of Water Resources Planning and Management 2010, 136(2):279-287.
63. Vrugt J.A., Gupta H.V., Bastidas L.A., Bouten W., Sorooshian S. Effective and efficient algorithm for multiobjective optimization of hydrologic models. Water Resources Research 2003, 39(8):1214. doi:1210.1029/2002WR001746.
64. Vrugt J.A., Diks C.G.H., Gupta H.V., Bouten W., Verstraten J.M. Improved treatment of uncertainty in hydrologic modeling: combining the strengths of global optimization and data assimilation. Water Resources Research 2005, 41:W01017. 01010.01029/02004WR003059.
65. Walsh J. Bounded probability properties of Kolmogorov-Smirnov and similar statistics for discrete data. Annals of the Institute of Statistical Mathematics 1963, 15(1):153-158.
66. Wang L., Fang L., Hipel K.W. Basin-wide cooperative water resources allocation. European Journal of Operational Research 2008, 190(3):798-817.
67. Weng S.Q., Huang G.H., Li Y.P. An integrated scenario-based multi-criteria decision support system for water resources management and planning - A case study in the Haihe River Basin. Expert Systems with Applications 2010, 37(12):8242-8254.
68. Ximing C. Implementation of holistic water resources-economic optimization models for river basin management - Reflective experiences. Environmental Modelling & Software 2008, 23(1):2-18.
69. Yandamuri S.R.M., Srinivasan K., Bhallamudi S.M. Multiobjective optimal waste load allocation models for rivers using nondominated sorting genetic algorithm-II. Journal of Water Resources Planning and Management 2006, 132(3):133-143.
70. Yapo P.O., Gupta H.V., Sorooshian S. Multi-objective global optimization for hydrologic models. Journal of Hydrology 1998, 204(1-4):83-97.
71. Zhang X., Srinivasan R., Zhao K., Liew M.V. Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model. Hydrological Processes 2009, 23(3):430-441.