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...

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Main Author:	, Widjajani
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/9600
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:9600
spelling	id-itb.:96002017-09-27T14:50:32ZPENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD , Widjajani Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/9600 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. text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
description	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.
format	Theses
author	, Widjajani
spellingShingle	, Widjajani PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
author_facet	, Widjajani
author_sort	, Widjajani
title	PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
title_short	PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
title_full	PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
title_fullStr	PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
title_full_unstemmed	PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD
title_sort	pengembangan model penjadwalan batch chemical process industry multiproduct dengan jaringan syaraf tiruan hopfield
url	https://digilib.itb.ac.id/gdl/view/9600
_version_	1820664742299041792

PENGEMBANGAN MODEL PENJADWALAN BATCH CHEMICAL PROCESS INDUSTRY MULTIPRODUCT DENGAN JARINGAN SYARAF TIRUAN HOPFIELD

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