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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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AN ENSEMBLE APPROACH OF METAHEURISTIC ALGORITHMS WITH PARABOLIC APPROXIMATION TO OPTIMIZE WELL PLACEMENT PROBLEM
Published 2021“…In previous research, classical and non-classical optimization techniques were used to solve well placement optimization problem. …”
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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique
Published 2008“…The new algorithm can effectively be used to tackle large scale optimization problems.Computational tests show promises of the new algorithm.…”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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A Biogeography-Based Optimization Algorithm Hybridized With Tabu Search For The Quadratic Assignment Problem
Published 2016“…Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. …”
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Artificial neural networks based optimization techniques: A review
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. …”
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A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem
Published 2016“…The quadratic assignment problem (QAP) is an NP hard combinatorial optimization problem with a wide variety of applications.Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems.It has been shown that BBO provides performance on a par with other optimization methods.A classical BBO algorithm employs the mutation operator as its diversification strategy. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA)
Published 2019“…This paper proposes Opposition-based Whale Optimization Algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. …”
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Ant colony optimization in dynamic environments
Published 2010“…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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Optimizing optimal path trace back system for Smith-Waterman algorithm using structural modelling technique: article
Published 2012“…back system for Smith-Waterman Algorithm using Structural Modelling Technique. The objectives for this paper are to optimize the best trace back scanning performance and also to design the simple architecture in order to reduce the runtime. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. …”
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm
Published 2020“…Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. …”
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