Solving flexible job-shop scheduling problem to minimize mean flow time using arithmetic optimization algorithm and rao-1 algorithm.
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The arithmetic optimization algorithm is a novel meta-heuristic algorithm.
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Meta- heuristic algorithms generally use randomness to determine the optimal solution for a wide range of problems as they can handle complex and nonlinear problems with large search spaces and find the global optimal solutions.
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To solve arithmetic problems, the suggested AOA method relies on the use of arithmetic operators.
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Rao algorithms are straightforward metaphor-free and tuning parameter-free optimization algorithms proposed by Rao (2020).
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After testing these algorithms on various optimization problems, Dr Rao claims that they give an effective solution to diverse optimization problems.
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However, the efficiency of these algorithms for difficult optimization problems is yet to be determined.
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The present work also focuses on improving and applying the Rao-1 method to solve FJSP, a complicated optimization problem, to minimize the mean flow-time, and comparing the results with those of other State-of-the-art models available in the literature review.