Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
This article has a reply.
VIEW THE REPLYThis article has a reply.
VIEW THE REPLYPublication: Journal of Water Resources Planning and Management
Volume 142, Issue 9
Abstract
Reservoir systems are essential for water resources management. The application and development of optimization techniques for optimal reservoir operation is therefore a valuable undertaking. This paper presents a modified firefly algorithm (MFA) and applies it to optimally solve reservoir operation problems. Three well-known benchmark multireservoir operation problems are optimized for energy production. The results of the MFA are compared with results obtained with other mathematical programming approaches, such as linear programming (LP), differential dynamic programming (DDP), and discrete DDP (DDDP), the genetic algorithm (GA), the multicolony ant algorithm (MCAA), the honey-bee mating optimization (HBMO) algorithm, the water cycle algorithm (WCA), the bat algorithm (BA), and the biogeography-based optimization (BBO) algorithm. The MFA was found to be more effective than alternative optimization methods in solving the test problems demonstrating its strong potential to tackle multireservoir operation problems. This paper’s results indicate that the MFA differed by 0.01 and 0.79% with the LP global optimal solutions of a continuous four-reservoir problem (CFP) and a continuous 10-reservoir problem (CTP), respectively. The objective function of a discrete four-reservoir problem (DFP) obtained with the MFA is equal to the LP’s objective function. This paper demonstrates that the MFA is a competitive optimization method with which to solve a variety of reservoir operation problems.
Get full access to this article
View all available purchase options and get full access to this article.
References
Afnizanfaizal, A., Safaai, D., MohdSaberi, M., and SitiZaiton, M. H. (2012). “A new hybrid firefly algorithm for complex and nonlinear problem.” Adv. Intell. Soft Comput., 151, 637–680.
Bozorg-Haddad, O., Afshar, A., and Mariño, M. A. (2011). “Multireservoir optimization in discrete and continuous domains.” Proc. Inst. Civ. Eng.: Water Manage., 164(2), 57–72.
Bozorg-Haddad, O., Hosseini-Moghari, S., and Loáiciga, H. A. (2016). “Biogeography-based optimization algorithm for optimal operation of reservoir systems.” J. Water Resour. Plann. Manage., 04015034.
Bozorg-Haddad, O., Karimirad, I., Seifollahi-Aghmiuni, S., and Loáiciga, H. A. (2015a). “Development and application of the bat algorithm for optimizing the operation of reservoir systems.” J. Water Resour. Plann. Manage., 04014097.
Bozorg-Haddad, O., Moravej, M., and Loáiciga, H. A. (2015b). “Application of the water cycle algorithm to the optimal operation of reservoir systems.” J. Irrig. Drain. Eng., 04014064.
Chow, V. T., and Cortes-Rivera, G. (1974). “Application of DDDP in water resources planning.”, Dept. of Civil Engineering, Univ. of Illinois, Urbana-Champaign, IL.
Farahani, S. M., Abshouri, A., Nasiri, B., and Meybodi, M. (2011). “A Gaussian firefly algorithm.” Int. J. Mach. Learn. Comput., 1(5), 448–453.
Fister, I., Yang, X. S., and Brest, J. (2013). “A comprehensive review of firefly algorithms.” Swarm Evol. Comput., 13(1), 34–46.
Heidari, M., Chow, V. T., Kokotovic, P. V., and Meredith, D. D. (1971). “Discrete differential dynamics programming approach to water resources system optimization.” Water Resour. Res., 7(2), 273–282.
HInçal, O., Altan-Sakarya, A. B., and Ger, A. M. (2011). “Optimization of multireservoir systems by genetic algorithm.” Water Resour. Manage., 25(5), 1465–1487.
Jalali, M. R., Afshar, A., and Mariño, M. A. (2007). “Multi-colony ant algorithm for continuous multi-reservoir operation optimization problem.” Water Resour. Manage., 21(9), 1429–1447.
Larson, R. E. (1968). State increment dynamics programming, Elsevier Science, New York.
Murray, D. M., and Yakowitz, S. J. (1979). “Constrained dynamic programming and its application to multireservoir control.” Water Resour. Res., 15(5), 1017–1027.
Wardlaw, R., and Sharif, M. (1999). “Evaluation of genetic algorithms for optimal reservoir system operation.” J. Water Resour. Plann. Manage., 25–33.
Yan, X., Zhu, Y., Wu, J., and Chen, H. (2012). “An improved firefly algorithm with adaptive strategies.” Adv. Sci. Lett., 16(1), 249–254.
Yang, X. S. (2008). “Firefly algorithm.” Nature-inspired meta-heuristic algorithms, Luniver Press, Bristol, U.K., 79–90.
Yang, X. S. (2009). “Firefly algorithm for multimodal optimization.” Stochastic Algorithms: Found. Appl., 5792(2), 169–178.
Yang, X. S. (2011). “Chaos-enhanced firefly algorithm with automatic parameter tuning.” J. Swarm Intell. Res., 2(4), 1–11.
Yang, X. S. (2014). Cuckoo search and firefly algorithm: Theory and applications, Springer, Switzerland.
Information & Authors
Information
Published In
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Jun 16, 2015
Accepted: Dec 9, 2015
Published online: May 4, 2016
Published in print: Sep 1, 2016
Discussion open until: Oct 4, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.