Search Results - (( parameter optimization based algorithm ) OR ( using case problems algorithm ))

Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Finally, two novel hybrid optimization algorithms namely, FLP-QOJaya algorithm for single objective OPF problems and MFLP-QOMJaya algorithm for MOOPF problems are proposed. …”
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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study by Got, Adel, Zouache, Djaafar, Moussaoui, Abdelouahab, Laith, Abualigah *, Alsayat, Ahmed

“…In this paper, the MRFO + SVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the SVM parameters and identify the optimal feature subset simultaneously. …”
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Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm by Mohd Annuar, Khalil Azha, Selamat, Nur Asmiza, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham

“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

“…A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Methodology for modified whale optimization algorithm for solving appliances scheduling problem by Omar, Mohd Faizal, Mohd Bakeri, Noorhadila, Mohd Nawi, Mohd Nasrun, Hairani, Norfazlirda, Khalid, Khalizul

“…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq by Al‑Aqeeli, Yousif H., Lee, Teang Shui, Abd Aziz, Samsuzana

“…In this case, the optimal values obtained from the GAOM were compared, firstly with their counterpart that found using the same algorithm without taking into consideration of Ev and Pr, secondly with the observed values. …”
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An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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Spread enhancement for firefly algorithm with application to control mechanism of exoskeleton system by Kasdirin, Hyreil Anuar, Ali, Siti Khadijah, Tokhi, M. O.

“…Firefly algorithm (FA) is a swarm intelligence based algorithm for global optimization and has widely been used in solving problems in many areas. …”
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

“…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

“…A heuristic method known as genetic algorithm is used to seek the optimum location and setting of these controllers where there are some works related to this case using various techniques. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm by Ng, Yeong Khang

“…To overcome the combinatorial optimization problem, Jaya algorithm is proposed to apply in this project since metaheuristic algorithm is fast in optimization and this strategy is named as CTJ. …”
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Profit-based optimal generation scheduling of a microgrid by Muhamad Razali N.M., Hashim A.H.

“…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”

Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

“…Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. …”
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