Search Results - optimal ((((robot algorithm) OR (bat algorithm))) OR (colony algorithm))*
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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…Swarm Intelligence is inspired by naturally occurring swarm systems suchas Ant Colony, Bees Hive, or Bats. The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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Multi-Robot Learning with Bat Algorithm With Mutation (Bam)
Published 2022“…Multiple techniques like swarm optimization, cuckoo algorithm and other such algorithms are under study for multi robotic systems. …”
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Undergraduates Project Papers -
3
Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm
Published 2022“…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
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Book Chapter -
4
Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam)
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Undergraduates Project Papers -
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PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)
Published 2019“…This algorithm is compared with a wellknown optimization algorithm, Particle Swarm Optimization (PSO). …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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Academic Exercise -
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A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
Published 2018“…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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Conference or Workshop Item -
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Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy
Published 2020“…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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Thesis -
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin
Published 2010“…This paper presents the application of Genetic Algorithm and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. …”
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A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning.
Published 2024“…Focusing on routing optimization, the study evaluates Ant-Colony Optimization (ACO) and Genetic Algorithm (GA) in Mobile Robot Planning. …”
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Conference or Workshop Item -
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…This will lead to the reduction of the energy consumption of the robot itself. The main goal of this research is to compare the performances between Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. …”
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Enhancement of ant colony optimization in multi-robot source seeking coordination
Published 2019“…In hardware platform, the speed of rotation of the wheel is controlled for various movement such as direct motion and rotation in place. Optimization method is focused on ant colony optimization. …”
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Proceedings -
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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Thesis -
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Comfort and energy consumption optimization in smart homes using bat algorithm with inertia weight
Published 2022“…Moreover, the comfort level achieved by BA with exponential inertia weight is found to be better than previously reported works using firefly algorithm, genetic algorithm, ant colony optimization, and artificial bee colony algorithm. …”
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Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm
Published 2019“…The robot prototype is able to move autonomously and optimized by the ant colony optimization with predefined position and terrain condition © BEIESP.…”
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Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization
Published 2019“…The selection of PTD gains for such system is highly difficult. Optimization of PID controller using Bat Algorithm (BA) is presented in this paper. …”
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Conference or Workshop Item -
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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Conference or Workshop Item -
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization
Published 2025“…In recent years, Automated Mobile Robots (AMRs) have gained significant attention in industry and research applications, requiring efficient path-planning algorithms to optimize task performance. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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