AN OPTIMIZED RESERVOIR OPERATION WITH STOCHASTIC ADAPTIVE REFINEMENT IN ANT ALGORITHMS

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AFSHAR M.H.; REZAEE SANGDEHI E.; MOEINI R.

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Journal Paper

Paper Information

Journal: IRAN-WATER RESOURCES RESEARCH Year:2010 | Volume:6 | Issue:1 (16) Page(s): 90-92

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Information Journal Paper

Title

AN OPTIMIZED RESERVOIR OPERATION WITH STOCHASTIC ADAPTIVE REFINEMENT IN ANT ALGORITHMS

Author(s)

AFSHAR M.H. | REZAEE SANGDEHI E. | MOEINI R. | Issue Writer Certificate

Keywords

ANT COLONY OPTIMIZATION

STOCHASTIC ADAPTIVE REFINEMENT

RESERVOIR OPERATION

Abstract

IntroductionMeta heuristics algorithms are usually used for the problems that are based on the behavior of real creatures. They basically try to combine basic heuristic methods in higher level frameworks aimed at efficiently and effectively exploring a search space. This class of algorithms includes Genetic Algorithms (GA), Iterated Local Search (ILS), Simulated Annealing (SA), Tabu Search (TS), ANT COLONY OPTIMIZATION (ACO), etc. ACO is a meta-heuristic approach proposed by Dorigo et al. (1991). The basic algorithm of ACO is Ant System (AS).

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APA: Copy

AFSHAR, M.H., REZAEE SANGDEHI, E., & MOEINI, R.. (2010). AN OPTIMIZED RESERVOIR OPERATION WITH STOCHASTIC ADAPTIVE REFINEMENT IN ANT ALGORITHMS. IRAN-WATER RESOURCES RESEARCH, 6(1 (16)), 90-92. SID. https://sid.ir/paper/579510/en

Vancouver: Copy

AFSHAR M.H., REZAEE SANGDEHI E., MOEINI R.. AN OPTIMIZED RESERVOIR OPERATION WITH STOCHASTIC ADAPTIVE REFINEMENT IN ANT ALGORITHMS. IRAN-WATER RESOURCES RESEARCH[Internet]. 2010;6(1 (16)):90-92. Available from: https://sid.ir/paper/579510/en

IEEE: Copy

M.H. AFSHAR, E. REZAEE SANGDEHI, and R. MOEINI, “AN OPTIMIZED RESERVOIR OPERATION WITH STOCHASTIC ADAPTIVE REFINEMENT IN ANT ALGORITHMS,” IRAN-WATER RESOURCES RESEARCH, vol. 6, no. 1 (16), pp. 90–92, 2010, [Online]. Available: https://sid.ir/paper/579510/en

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