Search Results - (( basic optimization strategy algorithm ) OR ( using solution using algorithm ))
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…There have been several scientific investigations in the past several decades on discovering effective and efficient algorithms to providing solutions to the optimization needs of mankind leading to the development of deterministic algorithms that provide exact solutions to optimization problems. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…There are two basic strategies in using hybrid GAs, Lamarckian and Baldwinian evolution. …”
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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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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems
Published 2022“…MRFO is a recently new introduced algorithm that consists of strategy of foraging adopted by Manta Ray while Gradient-based Mutation (GbM) is a feasibility-and solution repair strategy adopted from ϵ-Matrix-Adaptation Evolution Strategy (ϵ-MAES). …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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9
Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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Mathematical formulation of tabu search in combinatorial optimization
Published 2008“…CARP is known to be Non-deterministic Polynomialtime hard (NP-hard) where solutions are obtained through heuristic methods. Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. …”
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Monograph -
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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Determining optimal transportation allocation using linear programming methods / Tengku Mohd Hazimi Tuan Hassan and Maslin Masrom
Published 2022“…The efficiency and effectiveness of the transportation problem algorithm are determined using the Excel Solver. The excel solution and sensitivity analysis provide information about the optimal distribution strategy for their products. …”
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique
Published 2022“…An optimal solution was proposed by integrating fuzzy logic technique with brute force algorithm that gave the best system optimization, where the decision was based on the Satisfaction Ratio (SR) and State of Charge (SoC). …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture
Published 2021“…A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Tasks Distribution In Driver Scheduling Using Dynamic Set Of Bandwidth In Harmony Search Algorithm With 2-Opt
Published 2021“…The SBHS2-opt has guided searching strategy using heuristic concept or known as informed search. …”
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