Hybrid genetic algorithms and line search method for industrial production planning with non-linear fitness function
Many engineering,science,information technology and management optimization problems can be considered as non-linear programming real-world problems where all or some of the parameters and variables involved are uncertain in nature.These can only be quantified using intelligent computational techniq...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Published: |
PERGAMON
2009
|
| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/2038/1/PV100.pdf http://www.elsevier.com http://eprints.utp.edu.my/2038/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Many engineering,science,information technology and management optimization problems can be considered as non-linear programming real-world problems where all or some of the parameters and variables involved are uncertain in nature.These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic.The main objective of this research paper
is to solve non- linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers,which was represented by logistic membership functions using the hybrid evolutionary optimization approach.To explore the applicability of the present study,a numerical example is considered to determine the production planning for the decision variables and profit of the company. |
|---|