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Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
AbstractReservoir 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.
Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
AbstractReservoir 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.
Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
Bozorg-Haddad, Omid (author) / Garousi-Nejad, Irene / Loáiciga, Hugo A
2016
Article (Journal)
English
Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
| British Library Online Contents | 2016
Modified Firefly Algorithm for Solving Multireservoir Operation in Continuous and Discrete Domains
| Online Contents | 2016