A Genetic Algorithm Applied to Resource Management in Production Systems

1995 ◽  
pp. 101-111 ◽  
Author(s):  
Bogdan Filipič
Keyword(s):  
Genetic Algorithm ◽  
Resource Management ◽  
Production Systems

PERFORMANCE EVALUATION OF GENETIC DISTRIBUTED FUZZY CONTROLLERS FOR MULTI-PART-TYPE PRODUCTION LINE

2007 ◽  
Vol 06 (02) ◽  
pp. 115-128
Author(s):  
SEYED MAHDI HOMAYOUNI ◽  
TANG SAI HONG ◽  
NAPSIAH ISMAIL
Keyword(s):  
Genetic Algorithm ◽  
Performance Evaluation ◽  
Objective Function ◽  
Production Rate ◽  
Production Line ◽  
Production Systems ◽  
Membership Functions ◽  
Part Type ◽  
High Penalty ◽  
Single Part

Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable.

Optimal Inspection Allocation for Workstations of Attribute Data with Multi-Characteristics in Multi-Station Systems

2010 ◽  
Vol 450 ◽  
pp. 397-400
Author(s):  
Hsin Rau ◽  
Kuo Hua Cho ◽  
Yi Hsiang Wang
Keyword(s):  
Genetic Algorithm ◽  
Production Systems ◽  
Computation Time ◽  
Optimization Method ◽  
Type I ◽  
Type Ii ◽  
Profit Model ◽  
Serial Production ◽  
Attribute Data ◽  
Type Ii Errors

. The study models multi-characteristics inspection for inspection allocation problems with workstations of attribute data in serial production systems. Either 100% or 0% inspection is performed and Type I and Type II errors are considered. In addition, this study considers three possibilities of treatment of detected nonconforming units, namely, repair, rework and scrap. With the above considerations, a profit model is developed for optimally allocating inspections. Moreover, a genetic algorithm is used to solve the problem and it is proved to have much less computation time, compared with an optimization method based on complete enumeration, especially when number of workstations and characteristics becomes more.

Optimal energy and resource management in bio-production systems

1986 ◽  
Vol 20 (3) ◽  
pp. 161-174
Author(s):  
Syed A. Shah ◽  
Larry J. Kutz ◽  
Donald A. Bender
Keyword(s):  
Resource Management ◽  
Production Systems ◽  
Optimal Energy

scholarly journals Development of Production Simulator for Buffer Size Decisions in Complex Production Systems Using Genetic Algorithm

2007 ◽  
Vol 1 (3) ◽  
pp. 418-429 ◽  
Author(s):  
Jaber ABU QUDEIRI ◽  
Hidehiko YAMAMOTO ◽  
Rizauddin RAMLI ◽  
Khalid R. Al-MOMANI
Keyword(s):  
Genetic Algorithm ◽  
Production Systems ◽  
Buffer Size
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