Résumé:
In this paper, a new human-based metaheuristic algorithm called Technical and Vocational
Education and Training-Based Optimizer (TVETBO) is introduced to solve optimization problems.
The fundamental inspiration for TVETBO is taken from the process of teaching work-related skills
to applicants in technical and vocational education and training schools. The theory of TVETBO is
expressed and mathematically modeled in three phases: (i) theory education, (ii) practical education,
and (iii) individual skills development. The performance of TVETBO when solving optimization
problems is evaluated on the CEC 2017 test suite for problem dimensions equal to 10, 30, 50, and 100.
The optimization results show that TVETBO, with its high abilities to explore, exploit, and create a
balance between exploration and exploitation during the search process, is able to provide effective
solutions for the benchmark functions. The results obtained from TVETBO are compared with the
performances of twelve well-known metaheuristic algorithms. A comparison of the simulation results
and statistical analysis shows that the proposed TVETBO approach provides better results in most
of the benchmark functions and provides a superior performance in competition with competitor
algorithms. Furthermore, in order to measure the effectiveness of the proposed approach in dealing
with real-world applications, TVETBO is implemented on twenty-two constrained optimization
problems from the CEC 2011 test suite. The simulation results show that TVETBO provides an
effective and superior performance when solving constrained optimization problems of real-world
applications compared to competitor algorithms.
