A Discrete Teaching Learning Based Optimization Algorithm for Combinatorial Optimization Problems

Manal Zettam

doi:10.15866/iremos.v11i1.12788

A Discrete Teaching Learning Based Optimization Algorithm for Combinatorial Optimization Problems

Manal Zettam^(1*)

^(*) Corresponding author

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DOI: https://doi.org/10.15866/iremos.v11i1.12788

Abstract

The Teaching Learning Based Optimization algorithm is a population-based algorithm that was first designed for solving continuous optimization problems. A Discrete Teaching Learning Based Optimization algorithm is performed for combinatorial optimization problems in this paper. The proposed Discrete Teaching Learning Based Optimization algorithm uses a path-relinking strategy combined with a local search instead of the ways employed in the original Teaching Learning Based Optimization to move solutions within the search space. Moreover the exploration and exploitation stages were ensured by a Mean solution. The proposed algorithm was tested on 35 benchmarks of the cell formation problem. The results were satisfactory enough to classify the Discrete Teaching Learning Based Optimization algorithm among promising nature-inspired algorithms.
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Keywords

Teaching Learning Based Optimization; Cell Formation Problem

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