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Assembly sequence optimization using the bees algorithm
Published 2022“…In this study, the assembly sequence of a product was optimized by applying an algorithm known as the Bees Algorithm. …”
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Book Chapter -
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Application of the Bees Algorithm to find optimal drill path sequence
Published 2024“…These results show that the Bees Algorithm can be an alternative approach to find the optimal drilling sequence.…”
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Proceeding Paper -
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Optimization of drilling path using the bees algorithm
Published 2021“…The results comparison shows that the Bees Algorithm achieved comparable performance compared to other algorithms.…”
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Article -
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation
Published 2018“…However, very few strategies have been proposed for sequence-based t-way. This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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Thesis -
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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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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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches
Published 2015“…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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Conference or Workshop Item -
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T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm
Published 2019“…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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An optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2017“…This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. …”
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Thesis -
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments
Published 2026“…The CloudSim simulator is applied to evaluate each algorithm using key performance metrics, including makespan, average flow time, and the number of cloudlets that fail to meet deadlines. …”
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Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin
Published 2014“…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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Article -
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Cross-layer design using multi-channel system in WiMAX mesh networks
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Conference or Workshop Item -
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network
Published 2019“…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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A new minimum pheromone threshold strategy (MPTS) for max-min ant system
Published 2009“…Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. …”
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An exploration technique for the interacted multiple ant colonies optimization framework
Published 2024Conference Paper
