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201
EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
Published 2020“…These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) [sadiq et al., 1999] respectively. …”
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202
General iterative heuristics for VLSI multiobjective partitioning
Published 2003“…In this paper, we engineer two iterative heuristics for the optimization of VLSI netlist bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) and incorporate fuzzy rules in order to handle the multiobjective cost function. …”
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203
AI-Augmented Metasurface Synthesis for Dynamic Beam Steering in Reconfigurable Antenna Arrays
Published 2025“…As compared to the conventional heuristic methods, for example, genetic algorithms (GA), particle swarm optimization (PSO), the approach based on DRLs has rapid policy convergence, has relatively less computational latency, and is autonomous to adapt to dynamic wireless conditions. …”
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204
An evolutionary meta-heuristic for state justification insequential automatic test pattern generation
Published 2001“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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205
Parameterization and compensation of friction forces using geneticalgorithms
Published 1999“…A PI controller with parameters optimized using genetic algorithms is used to control the position of a DC motor with friction. …”
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206
Hybridizing rule-based power system stabilizers with geneticalgorithms
Published 1999“…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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207
Tuning of a fuzzy logic power system stabilizer using geneticalgorithms
Published 1997“…The proposed approach uses genetic algorithms (GA) to search for optimal or near optimal settings of fuzzy logic power system stabilizer (FLPSS) parameters. …”
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208
AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients
Published 2015“…In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. The performance of the three algorithms is evaluated on a data set found in the public UCMI repository.…”
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209
Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…We allocate newcomers to nodes with minimal computations and without changing the original optimized plan. The problem is solved using genetic algorithms that search within the feasible solution space. …”
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