NOVEL TRAIN HEIST OPTIMIZATION AND LOGISTIC CHAOTIC MAP BASED FRESHMAN LEARNING PROCESS INSPIRED ALGORITHM FOR SOLVING THE OPTIMAL POWER FLOW PROBLEM
DOI:
https://doi.org/10.55766/sujst-2024-04-e03588Keywords:
Terms-Train, Heist, Robbery, Gang, Logistic chaotic map, Freshman learning processAbstract
Train heist based optimization (THO) algorithm is designed based on the really happened train heist in United Kingdom. In the exploration section, robbery gang has been executed the plan has been imitated and mathematically defined. Prior to the execution the robbers plan the conspiracy after multiple examinations on the track. In the exploitation section fled activities of the robbery gang has been emulated and scientifically defined. Even though Leatherslade Farm had been already purchased by the robbery gang, they altered the plan rapidly with minimum stay period in the farm by listening in to the police very high frequencychannels. Chaotic communiqué amongst the gang members and Perception of movement may differ among the gang members and the error value in the decision of the movement is defined. Then in tis paper Logistic chaotic map based freshman learning process inspired optimization (LCP) algorithm is designed to solve the problem. LCP algorithm is designed by imitating the freshman learning process.Trainer will enhance learning processof freshman day by day. Freshman lives in ambiguous world and monetary predicament may originate at dissimilar phases of freshman’s life. Deeds of the freshman learning process are mathematically formulated and population engendered based on the logistic chaos mapping. Trainer will explore the complications and consider a mean point of all complications. Suitable guidance and solutions will be delivered to the freshman by the trainer. Train heist based optimization (THO) algorithm and Logistic chaotic map based freshman learning process inspired optimization (LCP) algorithm are validated in 23 Benchmarking functions and IEEE 30, 354 systems.
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