Loading…

Decentralized manufacturing management by a multi-agent optimal control method

A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production...

Full description

Saved in:
Bibliographic Details
Published in:Transactions of the Institute of Measurement and Control 2014-12, Vol.36 (8), p.935-945
Main Authors: Miranbeigi, M, Moshiri, B, Rahimi-Kian, A
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83
cites cdi_FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83
container_end_page 945
container_issue 8
container_start_page 935
container_title Transactions of the Institute of Measurement and Control
container_volume 36
creator Miranbeigi, M
Moshiri, B
Rahimi-Kian, A
description A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods or modelled using demand forecasting functions. In this paper, a new decentralized receding horizon control method is used to achieve customer contentment and low-cost inventory in a complete chain of supply, manufacture, assembly, warehouse, distribution and retail units. The main novelty of the method returns to the use of both the move suppression term and the look-ahead idea to increase robustness and smoothness in a supply chain containing assembly units. Also, a Kalman filter estimator is applied to estimate states and output variables. For this purpose, a suitable model and appropriate optimal control method are developed. Finally, the efficiency is indicated regarding simulation results.
doi_str_mv 10.1177/0142331214525799
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1686441305</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_0142331214525799</sage_id><sourcerecordid>3492272281</sourcerecordid><originalsourceid>FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83</originalsourceid><addsrcrecordid>eNp1kLtPwzAQxi0EEqWwM0ZiYQn4bWdE5SlVsMAc-ZWSyomLnQzlr8dRGFAlptPd9_tOdx8AlwjeICTELUQUE4IwogwzUVVHYIGoECUkvDoGi0kuJ_0UnKW0hRBSyukCvN474_ohKt9-O1t0qh8bZYYxtv1m6tTGdVkv9L5QRTf6oS3zKA_Cbmg75QsTsjv4onPDZ7Dn4KRRPrmL37oEH48P76vncv329LK6W5eGUDyU2AhFtLRcVZZL5UjlGkWllLix2lHGLdINwZAay6QhQnNtFCJIMeG0sJIswfW8dxfD1-jSUHdtMs571bswphpxySlFBLKMXh2g2zDGPl-XKYw5Z5DxTMGZMjGkFF1T72L-L-5rBOsp4Pow4GwpZ0vKifxZ-h__AymkeuY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1622665056</pqid></control><display><type>article</type><title>Decentralized manufacturing management by a multi-agent optimal control method</title><source>SAGE</source><creator>Miranbeigi, M ; Moshiri, B ; Rahimi-Kian, A</creator><creatorcontrib>Miranbeigi, M ; Moshiri, B ; Rahimi-Kian, A</creatorcontrib><description>A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods or modelled using demand forecasting functions. In this paper, a new decentralized receding horizon control method is used to achieve customer contentment and low-cost inventory in a complete chain of supply, manufacture, assembly, warehouse, distribution and retail units. The main novelty of the method returns to the use of both the move suppression term and the look-ahead idea to increase robustness and smoothness in a supply chain containing assembly units. Also, a Kalman filter estimator is applied to estimate states and output variables. For this purpose, a suitable model and appropriate optimal control method are developed. Finally, the efficiency is indicated regarding simulation results.</description><identifier>ISSN: 0142-3312</identifier><identifier>EISSN: 1477-0369</identifier><identifier>DOI: 10.1177/0142331214525799</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Assembly ; Control algorithms ; Decentralized ; Demand ; Forecasting ; Manufacturing ; Mathematical models ; Multiagent systems ; Optimal control ; Optimization techniques ; Supply chains</subject><ispartof>Transactions of the Institute of Measurement and Control, 2014-12, Vol.36 (8), p.935-945</ispartof><rights>The Author(s) 2014</rights><rights>SAGE Publications © Dec 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83</citedby><cites>FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27906,27907,79114</link.rule.ids></links><search><creatorcontrib>Miranbeigi, M</creatorcontrib><creatorcontrib>Moshiri, B</creatorcontrib><creatorcontrib>Rahimi-Kian, A</creatorcontrib><title>Decentralized manufacturing management by a multi-agent optimal control method</title><title>Transactions of the Institute of Measurement and Control</title><description>A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods or modelled using demand forecasting functions. In this paper, a new decentralized receding horizon control method is used to achieve customer contentment and low-cost inventory in a complete chain of supply, manufacture, assembly, warehouse, distribution and retail units. The main novelty of the method returns to the use of both the move suppression term and the look-ahead idea to increase robustness and smoothness in a supply chain containing assembly units. Also, a Kalman filter estimator is applied to estimate states and output variables. For this purpose, a suitable model and appropriate optimal control method are developed. Finally, the efficiency is indicated regarding simulation results.</description><subject>Assembly</subject><subject>Control algorithms</subject><subject>Decentralized</subject><subject>Demand</subject><subject>Forecasting</subject><subject>Manufacturing</subject><subject>Mathematical models</subject><subject>Multiagent systems</subject><subject>Optimal control</subject><subject>Optimization techniques</subject><subject>Supply chains</subject><issn>0142-3312</issn><issn>1477-0369</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp1kLtPwzAQxi0EEqWwM0ZiYQn4bWdE5SlVsMAc-ZWSyomLnQzlr8dRGFAlptPd9_tOdx8AlwjeICTELUQUE4IwogwzUVVHYIGoECUkvDoGi0kuJ_0UnKW0hRBSyukCvN474_ohKt9-O1t0qh8bZYYxtv1m6tTGdVkv9L5QRTf6oS3zKA_Cbmg75QsTsjv4onPDZ7Dn4KRRPrmL37oEH48P76vncv329LK6W5eGUDyU2AhFtLRcVZZL5UjlGkWllLix2lHGLdINwZAay6QhQnNtFCJIMeG0sJIswfW8dxfD1-jSUHdtMs571bswphpxySlFBLKMXh2g2zDGPl-XKYw5Z5DxTMGZMjGkFF1T72L-L-5rBOsp4Pow4GwpZ0vKifxZ-h__AymkeuY</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Miranbeigi, M</creator><creator>Moshiri, B</creator><creator>Rahimi-Kian, A</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SP</scope><scope>7U5</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>L7M</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><scope>7TB</scope></search><sort><creationdate>20141201</creationdate><title>Decentralized manufacturing management by a multi-agent optimal control method</title><author>Miranbeigi, M ; Moshiri, B ; Rahimi-Kian, A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Assembly</topic><topic>Control algorithms</topic><topic>Decentralized</topic><topic>Demand</topic><topic>Forecasting</topic><topic>Manufacturing</topic><topic>Mathematical models</topic><topic>Multiagent systems</topic><topic>Optimal control</topic><topic>Optimization techniques</topic><topic>Supply chains</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miranbeigi, M</creatorcontrib><creatorcontrib>Moshiri, B</creatorcontrib><creatorcontrib>Rahimi-Kian, A</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Science Journals</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering &amp; Technology Collection</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><jtitle>Transactions of the Institute of Measurement and Control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miranbeigi, M</au><au>Moshiri, B</au><au>Rahimi-Kian, A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decentralized manufacturing management by a multi-agent optimal control method</atitle><jtitle>Transactions of the Institute of Measurement and Control</jtitle><date>2014-12-01</date><risdate>2014</risdate><volume>36</volume><issue>8</issue><spage>935</spage><epage>945</epage><pages>935-945</pages><issn>0142-3312</issn><eissn>1477-0369</eissn><abstract>A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods or modelled using demand forecasting functions. In this paper, a new decentralized receding horizon control method is used to achieve customer contentment and low-cost inventory in a complete chain of supply, manufacture, assembly, warehouse, distribution and retail units. The main novelty of the method returns to the use of both the move suppression term and the look-ahead idea to increase robustness and smoothness in a supply chain containing assembly units. Also, a Kalman filter estimator is applied to estimate states and output variables. For this purpose, a suitable model and appropriate optimal control method are developed. Finally, the efficiency is indicated regarding simulation results.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/0142331214525799</doi><tpages>11</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0142-3312
ispartof Transactions of the Institute of Measurement and Control, 2014-12, Vol.36 (8), p.935-945
issn 0142-3312
1477-0369
language eng
recordid cdi_proquest_miscellaneous_1686441305
source SAGE
subjects Assembly
Control algorithms
Decentralized
Demand
Forecasting
Manufacturing
Mathematical models
Multiagent systems
Optimal control
Optimization techniques
Supply chains
title Decentralized manufacturing management by a multi-agent optimal control method
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T08%3A55%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Decentralized%20manufacturing%20management%20by%20a%20multi-agent%20optimal%20control%20method&rft.jtitle=Transactions%20of%20the%20Institute%20of%20Measurement%20and%20Control&rft.au=Miranbeigi,%20M&rft.date=2014-12-01&rft.volume=36&rft.issue=8&rft.spage=935&rft.epage=945&rft.pages=935-945&rft.issn=0142-3312&rft.eissn=1477-0369&rft_id=info:doi/10.1177/0142331214525799&rft_dat=%3Cproquest_cross%3E3492272281%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c342t-2c7a3b8d6a9d68ae39efa48882fdbe456d1bf3204cd58c37b6bca131a57eb7d83%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1622665056&rft_id=info:pmid/&rft_sage_id=10.1177_0142331214525799&rfr_iscdi=true