A Set of New Benchmark Optimization Problems for Water Resources Management

Water Resources Management

Volumn 27, Issue 9, 2013, Pages 3333-3348

  Karpouzos, Dimitrios K ^a   Katsifarakis, Konstantinos L ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Benchmark problem; Genetic algorithms; Optimization; Simulated annealing; Water resources management

Indexed keywords

BENCH-MARK PROBLEMS; COMPUTATIONAL VOLUME; ENGINEERING PROBLEMS; GLOBAL OPTIMAL SOLUTIONS; GROUNDWATER FLOW MODEL; HEURISTIC OPTIMIZATION; OPTIMIZATION PROBLEMS; WATER RESOURCES MANAGEMENT;

BENCHMARKING; GENETIC ALGORITHMS; GROUNDWATER; GROUNDWATER FLOW; OPTIMAL SYSTEMS; OPTIMIZATION; SIMULATED ANNEALING;

WATER RESOURCES;

BENCHMARKING; GENETIC ALGORITHM; GROUNDWATER FLOW; HEURISTICS; OPTIMIZATION; SIMULATED ANNEALING; WATER MANAGEMENT;

EID: 84878768022     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-013-0350-z     Document Type: Article

References (35)

1. Ali MM, Khompatraporn C, Zabinsky ZB (2005) A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems. J Global Optim 31(4): 635-672.
2. Bear J (1979) Hydraulics of Groundwater. McGraw-Hill.
3. Cerny V (1985) Thermodynamical approach to the travelling salesman problem: An efficient simulation algorithm. J Optim Theory Appl 45: 41-51.
4. Chiu Y-C, Nisshikawa T, Yeh WW-G (2010) Optimal Pump and Recharge Management Model for Nitrate Removal in the Warren Groundwater Basin. California J Water Resour Plann Manage 136(3): 299-308.
5. Cunha MC (2003) On Solving Aquifer Management Problems with Simulated Annealing Algorithms. Water Resour Manage 13: 153-170.
6. Deb K, Saha A (2010) Finding multiple solutions for multimodal optimization problems using multiobjective evolutionary approach. GECCO 2010: 447-454.
7. Dolan ED, Moré JJ (2002) Benchmarking optimization software with performance profiles. Math Program 91: 201-213.
8. Floudas CA, Pardalos PM (eds.) 2008 Encyclopedia of Optimization. 2nd edn. Kluwer Academic Publishers.
9. Floudas CA, Pardalos PM, Adjiman C, Esposito W, Gümüs Z, Harding S, Klepeis J, Meyer C, Schweiger C (1999) Handbook of Test Problems in Local and Global Optimization. Kluwer Academic Publishers, Dordrecht.
10. Fragoso T, Cunha MC, Lobo-Ferreira JP (2009) Optimal pumping from Palmela water supply wells (Portugal) using simulated annealing. Hydrogeol J 17(8): 1935-1948.
11. Gaviano M, Kvasov DE, Lera D, Sergeyev YD (2003) Algorithm 829: Software for generation of classes of test functionswith known of local and global minima for global optimization. ACM Trans Math Softw 29(4): 469-480.
12. Goldberg DE (2002) Design of innovation: lessons from and for competent genetic algorithms. Springer.
13. Ingber L (1993) Simulated annealing: practice versus theory. Math Comput Modell 18: 29-57.
14. Ji M, Jin Z, Tung H (2006) An improved simulated annealing for solving the linear constrained optimization problems. Appl Math Comput 183: 251-259.
15. Katsifarakis KL, Tselepidou K (2009) Pumping cost minimization in aquifers with regional flow and two zones of different transmissivities. J Hydrol 377(1-2): 106-111.
16. Katsifarakis KL, Karpouzos DK, Theodossiou N (1999) Combined use of BEM and genetic algorithms in groundwater flow and mass transport problems. Engin Anal Bound Elem 23(7): 555-565.
17. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by Simulated Annealing. Sci 4598: 671-680.
18. Kollat JB, Reed PM (2006) Comparison of multi-objective evolutionary algorithms for long-term monitoring design. Adv Water Resour 29(6): 792-807.
19. Koon GH, Sebald AV (1995) Some interesting test functions for evaluating evolutionary programming strategies. Proc fourth Annual Conf on Evolut. Program, San Diego, California, 1-3 March 1995, Evolutionary Programming IV, MIT Press, 479-499.
20. Liu JS, Caley AJ, Waddie AJ, Taghidech MR (2008) Comparison of simulated quenching algorithms for design of diffractive optical elements. Appl Opt 47(6): 807-816.
21. Matott LS, Bartelt-Hunt SL, Rabideau AJ, Fowler KR (2006) Application of heuristic optimization techniques and algorithm tuning to multilayered sorptive barrier design. Environ Sci Technol 40: 6354-6360.
22. Mayer AS, Kelley CT, Miller CT (2002) Optimal design for problems involving flow and transport in saturated porous media. Adv Water Resour 12: 1233-1256.
23. Nam D, Lee JS, Park CH (2004) N-dimensional Cauchy neighbour generation for the Fast Simulated Annealing. IEICE Trans Inf Syst E87-D(11): 2499-2502.
24. Reeves CR, Raw JE (2003) Genetic algorthms-Principles and perspectives. Kluwer Academic Publishers.
25. Shcherbina O, Neumaier A, Sam-Haroud D, Vu XH, Nguyen TV (2003) Benchmarking global optimization and constraint satisfaction codes. In: Global Optimization and Constraint Satisfaction. Lecture Notes in Computer Science 2861: 211-222.
26. Singh G, Deb K (2006) Comparison of multi-modal optimization algorithms based on evolutionary algorithms. GECCO 2006: 1305-1312.
27. Suman B, Kumar P (2006) A survey of simulated annealing as a tool for single and multiobjective optimization. J Oper Res Soc 57: 1143-1160.
28. Tang Y, Reed PM, Kollat JB (2007) Parallelization strategies for rapid and robust evolutionary multiobjective optimization in water resources applications. Adv Water Res 30: 335-353.
29. Teegavarapur RSV, Simonovic SP (2002) Optimal Operation of Reservoir Systems using Simulated Annealing. Water Resour Manage 16: 401-428.
30. Tsai FTC, Katiyar V, Toy D, Goff RA (2009) Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm. Water Resour Manage 23: 1497-1517.
31. Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1): 67-82.
32. Wu ZY, Walski T (2005) Self-adaptive penalty approach compared with other constraint-handling techniques for pipeline optimization. J Water Resour Plann Manage 131(3): 181-192.
33. Yang WY, Cao W, Chung TS, Morris J (2005) Applied numerical methods using Matlab. Hoboken, New Jersey, John Wiley & Sons, Inc.
34. Younis A, Dong Z (2010) Trends, features, and tests of common and recently introduced global optimization methods. Eng Optim 42(8): 691-718.
35. Youssef H, Sait SM, Adiche H (2001) Evolutionary algorithms, simulated annealing and tabu search: a comparative study. Eng Appl Artif Intell 14(2): 167-181.