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
[1] http://ieeexplore.ieee.org/document/7743919/
[2] http://ieeexplore.ieee.org/document/7744167/

Note:
(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.