Production scheduling optimization method for textile machinery manufacturing enterprise based on improved bee algorithm

2017 ◽  
Author(s):  
Li Xixing ◽  
Du Baigang ◽  
Guo Shunsheng ◽  
Xu Renhe
Keyword(s):  
Production Scheduling ◽  
Optimization Method ◽  
Scheduling Optimization ◽  
Manufacturing Enterprise ◽  
Bee Algorithm ◽  
Machinery Manufacturing

Method of Improving Production Scheduling Based on the Genetic Algorithm

2011 ◽  
Vol 411 ◽  
pp. 415-418
Author(s):  
Yong Gao ◽  
Ming Yu Li ◽  
Jian Ping Wang
Keyword(s):  
Genetic Algorithm ◽  
Production Scheduling ◽  
Model Simulation ◽  
Optimization Method ◽  
Production Model ◽  
Forward Simulation ◽  
Production Schedule ◽  
Scheduling Optimization ◽  
Simulation Data ◽  
Scheduling Model

In order to improve the inventory control efficiency and quality in manufacturing company, one production scheduling optimization method is put forward. Simulation of production model is firstly constructed, such as description of the production model, simulation data, machine processes and scheduling model. Moreover, Genetic Algorithm is applied to generate a production schedule for efficient running of machine. The simulation result is analyzed to verify the method by comparing product simulation with actual production.

Research on Production Scheduling Optimization with Utilization Ratio of Equipments

2012 ◽  
Vol 263-266 ◽  
pp. 3177-3183
Author(s):  
Fang Li ◽  
Yu Wang ◽  
Ying Chun Zhong ◽  
Zhi Tan
Keyword(s):  
Feeding Behavior ◽  
Production Scheduling ◽  
Optimization Method ◽  
Scheduling Optimization ◽  
Scheduling Model ◽  
Utilization Ratio

An optimization of multi-varieties and small-batch of production scheduling is proposed, which is embodied the utilization ratio of equipment. First, the production scheduling model with multi-varieties and small-batch is improved by adding a new constraint. Second, the feeding behavior, clustering and rear collision of artificial fish algorithm are improved in order to describe the multi-varieties and small-batch of production scheduling. Finally, the optimizing results influenced by iteration times and quantity of artificial fish are analyzed. The experiments show that the utilization ratio of equipments are nearly same and the Man Hour is decreased obviously while the optimization method is used, which testifies the validity of the new optimization method.

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