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Single Phase Multi-Group Teaching Learning Based Optimization

version (3.04 KB) by SKS Labs
SPMGTLO with termination criterion of maximum number of iterations


Updated 22 Jan 2018

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Single Phase Multi-Group Teaching Learning Based Optimization is a single objective optimization technique for unconstrained optimization problems. It is based on improved TLBO and employs only one functional evaluations per member of the population in a generation. Unlike TLBO, it does not require identification and elimination of duplicates and hence effectively utilizes the functional evaluations. SPMGTLO randomly divides the population into a specified number of groups containing equal number of population (except one group) and probabilistically employs either the teacher or the learner phase. Additional details including the advantages over TLBO and the performance on CEC competition can be obtained from

(i) Given T ierations and a population size of N, the total number of functional evaluations required is NT + N.

(ii) The user defined parameters are (a) the population size, (b) the number of generations and (c) the number of groups.

(iii) This implementation ensures monotonic convergence.

Cite As

SKS Labs (2022). Single Phase Multi-Group Teaching Learning Based Optimization (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired by: Teaching Learning Based Optimization

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