scholarly journals Hybrid Collaborative Multi-objective Fruit Fly Optimization Algorithm for Scheduling Workflow in Cloud Environment

2021 ◽  
pp. 101008
Author(s):  
Shuo Qin ◽  
Dechang Pi ◽  
Zhongshi Shao ◽  
Yue Xu
Keyword(s):  
Optimization Algorithm ◽  
Fruit Fly ◽  
Fruit Fly Optimization Algorithm ◽  
Cloud Environment ◽  
Fruit Fly Optimization ◽  
Multi Objective

scholarly journals A new cellular manufacturing layout: Multi-floor linear cellular manufacturing layout

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092530
Author(s):  
Yanlin Zhao ◽  
Jiansha Lu ◽  
Wenchao Yi
Keyword(s):  
Optimization Algorithm ◽  
Cellular Manufacturing ◽  
Fruit Fly ◽  
Intelligent Manufacturing ◽  
Population Diversity ◽  
Specific Reference ◽  
Fruit Fly Optimization Algorithm ◽  
Nsga Ii ◽  
Fruit Fly Optimization ◽  
Multi Objective

The article puts forward the new layout methodology of the multi-floor linear cellular manufacturing layout. The proposed equipment layout methodology not just breaks the conventional single-floor linear cellular manufacturing layout but also meets the layout requirements of the intelligent manufacturing workshop for the stereoscopic aisle manufacturing cell. The layout methodology takes into account the least space occupation as well as the shortest total distance of logistics as the objective function, besides considering the limitations that exist between the equipment, different planes, different levels, and so on; also, a mathematical model is put forward. The multi-floor linear cellular manufacturing layout is solved based on the self-adapting multi-objective fruit fly optimization algorithm that refers to an algorithm combining fruit fly optimization algorithm and NSGA-II. Self-adapting multi-objective fruit fly optimization algorithm makes use of the fast nondominated sorting for the multi-target food concentration calculation, together with designing the adaptive olfactory search and visual search, and employing the perturbation operations for flight strategies, aimed at ensuring the population diversity. Simulation cases suggest that self-adapting multi-objective fruit fly optimization algorithm has stronger advantages as compared with multi-objective fruit fly algorithm and elitist non-dominated sorting genetic algorithm (NSGA-II) in the solution of multi-floor linear cellular manufacturing layout problems. The final engineering case application sheds light on the fact that multi-floor linear cellular manufacturing layout saves 57.6% of the area, in addition to 23.7% of space, and 29.2% of the handling distance as compared with single-floor linear cellular manufacturing layout. Accordingly, multi-floor linear cellular manufacturing layout has a specific reference value in the layout of facilities in the intelligent manufacturing plants.

Adaptive chaos fruit fly optimization algorithm

2013 ◽  
Vol 33 (5) ◽  
pp. 1313-1316 ◽  
Author(s):  
Junying HAN ◽  
Chengzhong LIU
Keyword(s):  
Optimization Algorithm ◽  
Fruit Fly ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization
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