An Improved Harris Hawks Optimization Algorithm for Solving the Permutation Flow Shop Scheduling Problem

Authors

  • Xiaoyu Li

DOI:

https://doi.org/10.54097/

Keywords:

Permutation flow shop scheduling problem, Harris Hawks optimization, Minimize makespan

Abstract

In this paper, an improved Harris Hawks optimization algorithm is proposed to solve the permutation flow shop scheduling problem with the objective of minimizing the completion time. Logistic chaotic mapping and inverse learning strategy are used to generate a high-quality initial population. A golden sine algorithm is introduced to improve the position update method. A nonlinear escape energy factor and adaptive t-distribution strategy are introduced to solve the problem of imbalance between the exploration and exploitation phases of the HHO algorithm. The effectiveness of the improved Harris Hawks optimization algorithm is verified by testing it on the Reeves benchmark test set and comparing it with other algorithms.

References

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Published

30-04-2024

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Section

Articles

How to Cite

Li, X. (2024). An Improved Harris Hawks Optimization Algorithm for Solving the Permutation Flow Shop Scheduling Problem. Journal of Computing and Electronic Information Management, 12(3), 89-93. https://doi.org/10.54097/

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