PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
The dynamic changes in business environment nowadays force every kind of industry, inclusive chemical industry, to be more flexible and has quick and correct decision making ability in order to win the competition. Chemical industry, especially the Batch Chemical Process Industry (BCPI) which produc...
Saved in:
| Main Author: | |
|---|---|
| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/9600 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The dynamic changes in business environment nowadays force every kind of industry, inclusive chemical industry, to be more flexible and has quick and correct decision making ability in order to win the competition. Chemical industry, especially the Batch Chemical Process Industry (BCPI) which produce a lot of product at the same time, needs a quick response scheduling system to schedule its product operations effectively and efficiently This scheduling problem is an NP-Complete problem, and the time to solve an NP-complete problem will increase exponentially along with the increasing of products amount. This research suggested the new approach in BCPI scheduling which applied the Hopfield Artificial Neural Network to create a suboptimal schedule in a short time. |
|---|