Search Results - (( new evaluation search algorithm ) OR ( based optimization model algorithm ))
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Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…The multistate model is then implemented in PSO and GSA. As a consequence, multi-state particle swarm optimization (MSPSO) and multi-state gravitational search algorithm (MSGSA) are developed. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…The performance of Extended Virtual Force-Based Algorithm (EVFA) and Cuckoo Search (CS) algorithm are evaluated and EVFA shows the improvement of coverage area and exhibits a guaranteed connectivity compared to CS algorithm. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The proposed AGI-AntMiner algorithm is evaluated on 16 benchmark datasets of medical, financial, gaming and social domains obtained from the University California Irvine repository. …”
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Metaheuristic searching genetic algorithm based reliability assessment of hybrid power generation system
Published 2020“…The MSGA is based on a combination of metaheuristic scanning and Genetic Algorithm. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. The user participates in the search by proposing a new individual. …”
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Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Monograph -
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…A reactive ant colony optimization (RACO) algorithm has been proposed to overcome the limitations of the reactive search. …”
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Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
Published 2015“…The performance of the proposed distance evaluated SKF (DESKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). …”
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Conference or Workshop Item -
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem
Published 2022“…We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. …”
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Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
Published 2016“…This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. …”
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Conference or Workshop Item -
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The results of the proposed search-based test data generator show significant performance compared to the existing search-based test data generator.…”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. …”
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Book Chapter -
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…To achieve an optimum waiting and response time this thesis has proposed a new approach utilizing the aforementioned modelling, optimizing and partitioning algorithms. …”
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