An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling

Joint Authors

Wu, Peiliang
Chen, Wenbai
Mao, Bingyi
Yu, Hongnian
Yang, Qingyu

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-28

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Philosophy

Abstract EN

Due to the NP-hard nature, the permutation flowshop scheduling problem (PFSSP) is a fundamental issue for Industry 4.0, especially under higher productivity, efficiency, and self-managing systems.

This paper proposes an improved genetic-shuffled frog-leaping algorithm (IGSFLA) to solve the permutation flowshop scheduling problem.

In the proposed IGSFLA, the optimal initial frog (individual) in the initialized group is generated according to the heuristic optimal-insert method with fitness constrain.

The crossover mechanism is applied to both the subgroup and the global group to avoid the local optimal solutions and accelerate the evolution.

To evolve the frogs with the same optimal fitness more outstanding, the disturbance mechanism is applied to obtain the optimal frog of the whole group at the initialization step and the optimal frog of the subgroup at the searching step.

The mathematical model of PFSSP is established with the minimum production cycle (makespan) as the objective function, the fitness of frog is given, and the IGSFLA-based PFSSP is proposed.

Experimental results have been given and analyzed, showing that IGSFLA not only provides the optimal scheduling performance but also converges effectively.

American Psychological Association (APA)

Wu, Peiliang& Yang, Qingyu& Chen, Wenbai& Mao, Bingyi& Yu, Hongnian. 2020. An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling. Complexity،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1141240

Modern Language Association (MLA)

Wu, Peiliang…[et al.]. An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling. Complexity No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1141240

American Medical Association (AMA)

Wu, Peiliang& Yang, Qingyu& Chen, Wenbai& Mao, Bingyi& Yu, Hongnian. An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling. Complexity. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1141240

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1141240