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Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin
Published 2023“…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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Thesis -
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Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…This study focuses on "Comparative Analysis of Line Search Methods in SD Algorithm for Unconstrained Optimization Problems". …”
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Student Project -
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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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Conference or Workshop Item -
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Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation
Published 2019“…In order to enhance its accuracy and convergence rate, it is proposed to employ the Nelder and Mead (NM) method to implement the local search phase of the algorithm. …”
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Article -
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…This means A • algorithm only calculates and consider the next node m path that has the lowest value of G and F, plus searching the shortest route by using heuristic estimation in Manhattan method. …”
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Thesis -
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A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)
Published 2011“…The implementations of the three methods to solve TSP show that the RTS algorithm provides a better solution in terms of minimizing the objective function while SA algorithm is less time consuming in solving problem with large number of cities.In conclusion, RTS is more effective in producing good quality solution and on the other hand, SA may be used to obtain instant results.…”
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Monograph -
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Application of a primal-dual interior point algorithm using exact second order information with a novel non-monotone line search method to generally constrained minimax optimizatio...
Published 2008“…This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. …”
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Article -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Thesis -
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Multi-objective service restoration in distribution networks using genetic algorithm
Published 2013“…This thesis presents a new approach of supply restoration service using the Genetic Algorithm. The GA is robust in searching a global optimal solution for the large-scale combinatorial optimization problems. …”
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Thesis -
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…In particular, the search capacity of the MVO algorithm has been improved using the sine and cosine functions of the Sine Cosine Algorithm (SCA) that will be able to balance the processes of exploration and exploitation. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Thesis -
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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Application of adaptive bats sonar algorithm to minimise car side impact design
Published 2017“…The best objective function was compared with the existing results of other swarm intelligence algorithms. …”
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Undergraduates Project Papers -
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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Thesis -
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Note that the 18-bus system is originally without any capacitor. Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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An improved particle swarm optimization based on lévy flight and simulated annealing for high dimensional optimization problem
Published 2022“…The proposed algorithm uses two strategies to address high-dimensional problems: hybrid PSO to define the global search area and fast simulated annealing to refine the visited search region. …”
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Article -
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Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates
Published 2023“…Results prove that the algorithm is reliable and could be easily implemented even on a much complex and nonconvex problems. � 2012 Elsevier Ltd. …”
Article -
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Recently, an attractive bio-inspired method—namely the Artificial Bee Colony (ABC)—has shown outstanding performance with some typical computational algorithms in different complex problems. …”
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Article -
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…This novel optimization method is a direct search approach and is usually directed to solve nonlinear optimization problems that may not have well-known derivatives, and it is called the Nelder-mead Method (NMM). …”
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