A Multi-objective Particle Swarm Optimization Algorithm Embedded with Maximum Fitness Function for Dual-Resources Constrained Flexible Job Shop Scheduling-Reference-Cited by-同舟云学术

A Multi-objective Particle Swarm Optimization Algorithm Embedded with Maximum Fitness Function for Dual-Resources Constrained Flexible Job Shop Scheduling

Published:2021 Issue: Volume: Page:725-738
ISSN:0302-9743
Container-title:Intelligent Computing Theories and Application
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Author:

Zhang Jing,Jie Jing

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-84522-3_59

Reference31 articles.

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3. Xiong, L., Qian, Q., Yunfa, F.: Review of application of genetic algorithms for solving flexible job shop scheduling problems. Comput. Eng. Appl. 55(23), 15–22 (2019)

4. Elmaraghy, H., Patelb, V., Abdallaha, I.B.: A genetic algorithm based approach for scheduling of dual-resource constrainded manufacturing systems. J. Manuf. Syst. 48(1), 369–372 (1999)

5. Deb, K.: A fast elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2000)

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