scholarly journals Solution of Co-evolution Self-adaptive Genetic Algorithm to Production Scheduling Problem of Flexible Manufacturing System

2016 ◽  
Author(s):  
Yun Zou ◽  
Guo-fu Yin
Keyword(s):  
Genetic Algorithm ◽  
Production Scheduling ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Adaptive Genetic Algorithm ◽  
Scheduling Problem ◽  
Self Adaptive

Scheduling Research of AGV with Double Buffers Based Genetic Algorithm in Flexible Manufacturing System

2011 ◽  
Vol 121-126 ◽  
pp. 1630-1635
Author(s):  
Nai Fei Ren ◽  
Yan Zhao ◽  
Jun Zhang
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Scheduling Problem ◽  
Improved Genetic Algorithm ◽  
System A ◽  
Fms Scheduling ◽  
Moving Path ◽  
Made In

Aiming at solving scheduling problem of flexible manufacturing system, this paper puts forward a FMS scheduling problem where single AGV with two buffers system is to be considered. Such an AGV with two buffers system was replaced with double-buffer AGV system in the next content. To solve FMS scheduling problem with double-buffer AGV system, a mathematical model which integrated double-buffer AGV and jobs was designed. And an improved genetic algorithm is proposed to sequence processing of jobs and the moving path of double-buffer AGV. The experiments made in simulation FMS production line laboratory realized scheduling integration of jobs and AGV, meanwhile, experiments gained processing sequence of jobs on each machine and moving path of AGV. Contrasting results of double-buffer and no-buffer AGV system verified double-buffer AGV system has higher feasibility and effectiveness.

scholarly journals Minimization of Machine Idle Time and Penalty Cost in Flexible Manufacturing System Scheduling

2019 ◽  
Vol 8 (6) ◽  
pp. 483-487
Keyword(s):  
Objective Function ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Cuckoo Search ◽  
Scheduling Problem ◽  
Jaya Algorithm ◽  
Penalty Cost ◽  
Paper Address ◽  
Better Than

This paper address the application of Jaya algorithm to solve Multi objective scheduling problem in Flexible Manufacturing System(FMS) to Minimize the Combined Objective Function(COF) Value. The effectiveness of this algorithm is tested on the problem of 43 jobs processed on 16 machines taken from literature. The MATLAB code is written to find best sequence and Combined Objective Function value by implementing Jaya Algorithm. Results obtained by Jaya Algorithm are compared with different algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Shortest Processing Time (SPT), Cuckoo Search (CS) and Modified Cuckoos Search (MCS) for the problem considered. It is observed from the results that COF value for the sequence obtained by Jaya Algorithm is better than other algorithms. It is concluded that the Jaya algorithm is best suitable for solving the Scheduling problem considered in Flexible Manufacturing System.

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