Search Results - intelligence based ((((bees algorithm) OR (search algorithm))) OR (graph algorithm))

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  1. 1

    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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  2. 2

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. …”
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    Thesis
  3. 3

    Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm by Abed, S.A., Rais, H.M.

    Published 2020
    “…This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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    Article
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    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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  6. 6

    Hybrid bat algorithm for minimum dominating set problem by Abed, S.A., Rais, H.M.

    Published 2017
    “…In this paper, the stochastic search represented by hybrid swarm intelligence algorithm to find the smallest set of nodes that dominate the graph. …”
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    Article
  7. 7

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…This paper proposes a new meta-heuristic approach to solving numerical and graph-based problems. The African buffalo algorithm evolved from an understanding of the animal's survival instincts and the search techniques they utilize in the African forests and savannahs; the search for the optimal path to pasture is aligned to their cooperative, intelligent, and social nature. …”
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    Article
  8. 8

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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  12. 12

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOO approaches include scalarization, Pareto dominance, decomposition and indicator-based. In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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    Article
  13. 13

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
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    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…The bees are classified into three agents: the employed bee which carries the information about the food source, the onlooker bee watching the dance of the employed bees within the hive and making the decision to choose a food source based on the dances, and the scout bee, performing random search for the food sources. …”
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    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
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    Utilization of Tabu search heuristic rules in sampling-based motion planning by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M.

    Published 2023
    “…We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. …”
    Conference Paper