Search Results - (( solution equalization based algorithm ) OR ( program implementation using algorithmic ))
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1
Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli
Published 2017“…Experimental result shows that my three-dimensional array staffscheduling implementation based on the best problem solution of the minimum violated working time of each staff works for 28 days equally to avoid overpay.…”
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2
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two methods of load flow solution with different accuracy are employed, i.e., simplified method, which uses the approximation of P and Q at the start of the implemented program, and fast-decoupled method, which gives an exact solution. …”
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3
Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong
Published 2018“…The computational results also show that the algorithms of population based ACO performs better than the algorithms of non-population based ACO. …”
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4
Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation
Published 2020“…Addressing the aforementioned issues, this research proposes the development and implementation of hybrid t-way strategy based Migrating Birds Optimization Algorithm (MBO) and Genetic Algorithm (GA) with elitism, termed Elitist Hybrid MBO-GA. …”
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5
Family of singly diagonally implicit block backward differentiation formulas for solving stiff ordinary differential equations
Published 2021“…The strategy is to reduce a fully implicit method to lower triangular matrix with equal diagonal elements. In order to achieve a particular order of accuracy, error norm minimization strategy is implemented based on the error constant of the formulas. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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Enhancing the Sorting Layers in the Initial Stage of High School Timetabling
Published 2020“…KHE is an algorithm that generates initial solution of HSTP. …”
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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm
Published 2018“…The proposed algorithm is applicable to all levels of MLI having equal and non-equal DC sources. …”
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Adjusted 0-1 knapsack problem in cargo flow by using artificial bee colony algorithm / Nor Zuliiziati Md Jani
Published 2021“…With its total value as much as possible, the number of items that may become less or at least equal to or equal to the limit. The aim of this research is to determine the flow of the shipment based on volume and to determine the total cost based on the flow of shipment by using Artificial Bee Colony (ABC) algorithm. …”
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Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization
Published 2015“…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
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Implementation of autonomous vehicle navigation algorithms using event-driven programming
Published 2012“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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14
A COMPUTATIONAL ALGORITHM for the NUMERICAL SOLUTION of NONLINEAR FRACTIONAL INTEGRAL EQUATIONS
Published 2022“…In this paper, we develop a numerical method for the solution of nonlinear fractional integral equations (NFIEs) based on Haar wavelet collocation technique (HWCT). …”
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Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad
Published 2002“…The method has been implemented as a C programming language. In this study, Wagner and Fischer algorithm, Hadith test collection that consists of Malay Hadith translation documents, query words and relevant judgements are used. …”
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Adjusted 0-1 knapsack problem in cargo flow by using artificial bee colony algorithm / Siti Hafawati Jamaluddin ... [et al.]
Published 2022“…With its total value as much as possible, the number of items that may become less or at least equal to or equal to the limit. Therefore, the aim of this study is to determine the minimum total cost of 30 shipments based on volume by using Artificial Bee Colony (ABC) algorithm in order to achieving the highest profit. …”
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Multi-Swarm bat algorithm
Published 2023“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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Enhancing CI engine performance and emission control using a hybrid RSM–Rao algorithm for ZnO-doped castor–neem biodiesel blends
Published 2025“…The former algorithm possesses the aforementioned features. Rao's algorithm does not mimic the behaviour of swarms, animals, birds, or any physical or chemical phenomenon, but it provides effective solutions to complicated problems. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…One of these MOO algorithms Multi-Objective Particle Swarm Optimization (MOPSO) extends it to handle problems with multiple objectives simultaneously, but like many swarm-based algorithms, MOPSO can suffer from premature convergence or local optima solutions. …”
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