Development of the enhanced self-adaptive hybrid genetic algorithm (e-SAHGA)

Water Resources Research

Volumn 42, Issue 8, 2006, Pages

  Espinoza, Felipe P ^a,b   Minsker, Barbara S ^a  

^a University of Illinois at Urbana Champaign   (United States)

^b U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; GENETIC ALGORITHMS; GROUNDWATER RESOURCES; POPULATION STATISTICS;

ENHANCED SELF ADAPTIVE HYBRID GENETIC ALGORITHM (E-SAHGA); GROUNDWATER REMEDIATION;

WATER POLLUTION CONTROL;

COMPUTATION THEORY; GENETIC ALGORITHMS; GROUNDWATER RESOURCES; POPULATION STATISTICS; WATER POLLUTION CONTROL;

GENETIC ALGORITHM; GROUNDWATER; REMEDIATION;

EID: 33749385471     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2005WR004221     Document Type: Article

References (21)

1. Aguado, E., I. Remson, M. F. Pikul, and W. A. Thomas (1974), Optimum pumping for aquifer dewatering, J. Hydraul. Div. Am. Soc. Gv. Eng., 100, 860-877.
2. Aly, A. H., and R. C. Peralta (1999), Comparison of a genetic algorithm and mathematical programming to the design of groundwater cleanup systems, Water Resour. Res., 35(8), 2415-2425.
3. Chan Hilton, A. B., and T. B. Culver (2000), Constraint handling for genetic algorithms in optimal remediation design, J. Water Resour. Plann. Manage., 126(3), 128-137.
4. Dougherty, D. E., and R. A. Marryott (1991), Optimal groundwater management: 1. Simulated annealing, Water Resour. Res., 27(10), 2493-2508.
5. Espinoza, F. (2003), A self-adaptive hybrid genetic algorithm for groundwater remediation design, Ph.D. dissertation, Dep. of Civ. and Environ. Eng., Univ. of Ill. at Urbana-Champaign, Urbana.
6. Espinoza, F., B. S. Minsker, and D. Goldberg (2005), An adaptive hybrid genetic algorithm for groundwater remediation design, J. Water Resour. Plann. Manage., 131(1), 14-24.
7. Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimizations and Machine Learning, Addison-Wesley, Boston, Mass.
8. Gopalakrishnan, G., B. S. Minsker, and D. E. Goldberg (2003), Optimal sampling in a noisy genetic algorithm for risk-based remediation design, J. Hydroinf., 5(1), 11-25.
9. Gorelick, S. M., C. I. Voss, P. E. Gill, W. Murray, M. A. Saunders, and M. H. Wright (1984), Aquifer reclamation design: The use of contaminant transport simulation combined with nonlinear programming, Water Resour. Res., 20(4), 415-427.
10. Hogg, R., and A. Craig (1978), Introduction to Mathematical Statistics, Macmillan, New York.
11. Hsiao, C., and L. Chang (2002), Dynamic optical groundwater management with inclusion of fixed costs, J. Water Resour. Plann. Manage., 128(1), 57-65.
12. Kapelan, Z. S., D. A. Savic, and G. A. Walters (2000), Inverse transient analysis in pipe networks for leakage detection and roughness calibration, Proceedings of Water Network Modelling for Optimal Design and Management, vol. 1, edited by D. A. Savic and G. A. Walter, pp. 143-159, Cent. for Water Syst., Univ. of Exeter, Exeter, U. K.
13. Kapelan, Z. S., D. A. Savic, and G. A. Walters (2002), Hybrid GA for calibration of water distribution hydraulic models, paper presented at 2002 Conference on Water Resources Planning and Management, Environ, and Water Resour. Inst. of the Am. Soc. of Civ. Eng., Blacksburg, Va.
14. Lefkoff, L. J., and S. M. Gorelick (1986), Design and cost analysis of rapid aquifer restoration systems using flow simulation and quadratic programming, Ground Water, 24(6), 777-790.
15. Marryott, R. A., D. E. Dougherty, and R. L. Stollar (1993), Optimal groundwater management: 2. Application of simulated annealing to a field-scale contamination site, Water Resour. Res., 29(4), 847-860.
16. Minsker, B. S., and C. A. Shoemaker (1998), Computational issues for optimal in-situ bioremediation design, J. Water Resour. Plann. Manage., 124(1), 39-46.
17. Partheepan, R. (2003), Hybrid genetic algorithms, M.S. thesis, Dep. of Civ. Eng., N.C. State Univ., Raleigh.
18. Smalley, J. B., B. S. Minsker, and D. E. Goldberg (2000), Risk-based in situ bioremediation design using a noisy genetic algorithm, Water Resour. Res., 36(20), 3043-3052.
19. Yu, D. M., M. Rizzo, and D. E. Dougherty (1998), Multi-period objectives and groundwater remediation using SAMOA: Tandem simulated annealing and external cutting plane method for containment with cleanup, in XII International Conference on Computational Methods in Water Resources, Crete, Greece, edited by V. N. Burganos et al., pp. 332-340, Comput. Mech., Billerica, Mass.
20. Zheng, C., and P. P. Wang (1999), An integrated global and local optimization approach for remediation system design, Water Resour. Res., 35(1), 137-148.
21. Zheng, C., and P. P. Wang (2002), A field demonstration of the simulation-optimization approach for remediation system design, Ground Water, 40(3), 258-265.