Search Results - (( java simulation optimization algorithm ) OR ( construct optimization search algorithm ))
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The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem
Published 2019“…We propose an algorithm that simplifies the search operation to only randomized population initialization following the Randomized Incremental Construction Technique, which essentially compartmentalizes optimization into smaller sub-units. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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A new HMCR parameter of harmony search for better exploration
Published 2016“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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A new HMCR parameter of harmony search for better exploration
Published 2015“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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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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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem
Published 2021“…The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. …”
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Virtual Force Algorithm and Cuckoo Search algorithm for node placement technique in wireless sensor network
Published 2013“…Wireless Sensor Network (WSN) has become one of the current technologies in the world of information technology.Coverage and connectivity are the main requirement that reflects the performance and quality of services in WSN applications.In WSN applications with a large scale area, the sensor nodes are deployed randomly in a noninvasive way.The deployment process will cause some issues such as coverage hole and overlapping that reflect to the performance of coverage area and connectivity.Node placement model is constructed to find the optimal node placement.Virtual Force Algorithm (VFA) and Cuckoo Search (CS) algorithm approach for node placement technique is analyzed to find the optimal node placement in order to improve the network coverage and connectivity with a minimum coverage hole and overlapping area.…”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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A Pairwise Test Suite Generator based on Melody Search Algorithm
Published 2016“…Abstract. Melody Search Algorithm (MS) has been adopted to solve many optimization problems such as combinatorial testing. …”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The aim of this paper is to exploit the capability of bio-inspired search algorithms, together with wrapper and filtered methods in generating optimal set of features. …”
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A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling
Published 2025“…This research enhances HSA by hybridizing it with the Great Deluge Algorithm (GDA) using a four-phase methodology. In Phase 1, heuristic rules refine the time assignment stage to improve an existing construction algorithm. …”
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