Search Results - (( variable optimization path algorithm ) OR ( evolution optimisation based algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

“…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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Path optimization using genetic algorithm in laser scanning system by Chen, Chai Phing, Koh, Johnny Siaw Paw, Aris, Ishak, Fong, Albert Yu Chooi, Tiong, Sieh Kiong

“…In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. …”
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Path optimization using genetic algorithm in laser scanning system by Chen C.P., Koh S.P., Aris I.B., Albert F.Y.C., Tiong S.K.

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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

“…Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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Runtime reduction in optimal multi-query sampling-based motion planning by Khaksar W., Sahari K.S.B.M., Ismail F.B., Yousefi M., Ali M.A.

A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

“…However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. …”

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

“…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. …”
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Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

“…Here, a routing tree is constructed based on the energy/bit minimization routing (EbMR). This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.…”
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Resource Efficient For Hybrid Fiber-Wireless Communications Links In Access Networks With Multi Response Optimization Algorithm by Wong, Adam Yoon Khang, Indra, Win Adiyansyah, Jamil Alsayaydeh, Jamil Abedalrahim, Mohamat Gani, Johar Akbar, M. Idrus, Sevia, Pusppanathan, Jaysuman

“…This work proposes a Multi response Optimization (MO) algorithm, named MO-LMMHOWAN that apply in Last Mile Mobile Hybrid Optical Wireless Access Network (LMMHOWAN). …”
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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

“…This research presents the optimal switching sequence path to minimize power losses during the network switching operation. …”
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