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

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

“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
Get full text
Get full text
Get full text

Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

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

Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

Get full text
Get full text

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

“…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. …”
Get full text
Get full text
Get full text
Get full text

Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

“…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. …”
Get full text
Get full text

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

“…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. …”
Get full text
Get full text

Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…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. …”
Get full text
Get full text

Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

“…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
Get full text
Get full text

Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

“…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
Get full text
Get full text
Get full text
Get full text

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

“…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. …”
Get full text
Get full text

Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

Get full text
Get full text

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.

“…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. …”

A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

Get full text
Get full text
Get full text

Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

“…In both algorithms, global searching is performed by APSO algorithm. …”
Get full text
Get full text
Get full text

Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy by Hossain Md.S., El-Shafie A., Mohtar W.H.M.W.

A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

“…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
Get full text
Get full text

Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok

“…The fitness-dependent optimizer (FDO), a newly proposed swarm intelligent algorithm, is focused on the reproductive mechanism of bee swarming and collective decision-making. …”
Get full text
Get full text
Get full text

Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

Get full text
Get full text

Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…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. …”
Get full text
Get full text
Get full text

Evaluating JA-ABC5 hyperparameter optimisation with classifiers by Ravindran, Nadarajan, Noorazliza, Sulaiman, Junita, Mohamad-Saleh

“…Because of its simplicity, flexibility, and robustness, the Artificial Bee Colony (ABC) algorithm, a swarm intelligence-based optimisation method, has been widely applied in a variety of fields. …”
Get full text
Get full text
Get full text