Fuzzy logic control of aggregate production planning
Rinks used linguistic variables of the sort proposed by Zadeh for cost, inventory, production, and work force. He operated on these with fuzzy if-ten rules in a manner like that used by Mamdani and Assilan to control a steam engine. The Rinks membership functions and rules were subjective creations....
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Veröffentlicht in: | Computers & industrial engineering 1992-11, Vol.23 (1), p.137-140 |
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creator | Ward, T.L. Ralston, P.A.S. Davis, J.A. |
description | Rinks used linguistic variables of the sort proposed by Zadeh for cost, inventory, production, and work force. He operated on these with fuzzy if-ten rules in a manner like that used by Mamdani and Assilan to control a steam engine. The Rinks membership functions and rules were subjective creations. Nevertheless, he obtained results that compared favorably to both prior and subsequent heuristic treatments of the HMMS data. We have developed a C language fuzzy logic controller (FLC) that uses the Rinks discrete membership functions and closely reproduces his results. We have used this FLC to investigate the effect of granularity of the discretization on the quality of solution. We have also used Wang-Mendel learning to improve the rule base. This paper discusses these results and suggests areas for further investigation. |
doi_str_mv | 10.1016/0360-8352(92)90082-U |
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He operated on these with fuzzy if-ten rules in a manner like that used by Mamdani and Assilan to control a steam engine. The Rinks membership functions and rules were subjective creations. Nevertheless, he obtained results that compared favorably to both prior and subsequent heuristic treatments of the HMMS data. We have developed a C language fuzzy logic controller (FLC) that uses the Rinks discrete membership functions and closely reproduces his results. We have used this FLC to investigate the effect of granularity of the discretization on the quality of solution. We have also used Wang-Mendel learning to improve the rule base. This paper discusses these results and suggests areas for further investigation.</description><subject>Algorithms</subject><subject>Applications</subject><subject>Applied sciences</subject><subject>Controllers</subject><subject>Exact sciences and technology</subject><subject>Fuzzy logic</subject><subject>Logic</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Operations research</subject><subject>Planning. 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Forecasting</topic><topic>Production planning</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ward, T.L.</creatorcontrib><creatorcontrib>Ralston, P.A.S.</creatorcontrib><creatorcontrib>Davis, J.A.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & industrial engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ward, T.L.</au><au>Ralston, P.A.S.</au><au>Davis, J.A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy logic control of aggregate production planning</atitle><jtitle>Computers & industrial engineering</jtitle><date>1992-11-01</date><risdate>1992</risdate><volume>23</volume><issue>1</issue><spage>137</spage><epage>140</epage><pages>137-140</pages><issn>0360-8352</issn><eissn>1879-0550</eissn><coden>CINDDL</coden><abstract>Rinks used linguistic variables of the sort proposed by Zadeh for cost, inventory, production, and work force. 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subjects | Algorithms Applications Applied sciences Controllers Exact sciences and technology Fuzzy logic Logic Operational research and scientific management Operational research. Management science Operations research Planning. Forecasting Production planning Studies |
title | Fuzzy logic control of aggregate production planning |
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