Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness
This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family spli...
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| Veröffentlicht in: | International journal of production research 2014-01, Vol.52 (19), p.5656-5674 |
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| container_title | International journal of production research |
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| creator | Süer, Gürsel A. Ates, Ozan K. Mese, Emre M. |
| description | This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper. |
| doi_str_mv | 10.1080/00207543.2014.903343 |
| format | Article |
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The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. 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The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.</description><subject>cell scheduling</subject><subject>Due dates</subject><subject>Genetic algorithms</subject><subject>group scheduling</subject><subject>Heuristic</subject><subject>heuristics</subject><subject>Manufacturing cells</subject><subject>Mathematical models</subject><subject>mixed integer linear programming</subject><subject>Optimization</subject><subject>Production scheduling</subject><subject>Scheduling</subject><subject>Splitting</subject><subject>Studies</subject><issn>0020-7543</issn><issn>1366-588X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kE1rGzEQhkVJoY7bf9CDIJde1pVWH949lWDyUQjk0kJvYrwaxTLalSvt1vW_jxYnlxyii2B45uWdh5CvnK04a9h3xmq2VlKsasblqmVCSPGBLLjQulJN8-eCLGakmplP5DLnPStPNXJBug2GQEME64cnCoOlDnofTjR3O7RTmKcuJrqP20yPftxRP1j_z9sJArUTUgsjZjpG2vvB9z4j7eG_76eejpBKKOb8mXx0EDJ-efmX5Pftza_NffXwePdzc_1QdVK3Y-Wc4wJqqdbcNqx0h04yKbeaI7dSCWDWKXRlpp22LVqLrdwycIhOIO_Eknw75x5S_DthHk3p05X7YMA4ZcO1bltWc9UU9OoNuo9TGko7w5VmvFalRaHkmepSzDmhM4fke0gnw5mZzZtX82Y2b87my9qP85ofiroejjEFa0Y4hZhcgqHz2Yh3E54BG-GLAQ</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Süer, Gürsel A.</creator><creator>Ates, Ozan K.</creator><creator>Mese, Emre M.</creator><general>Taylor & Francis</general><general>Taylor & Francis LLC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20140101</creationdate><title>Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness</title><author>Süer, Gürsel A. ; Ates, Ozan K. ; Mese, Emre M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c469t-fff13a24571d80366ac4044b61e1d453a0df5ef4046f6d9edde94b0afeef3e1c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>cell scheduling</topic><topic>Due dates</topic><topic>Genetic algorithms</topic><topic>group scheduling</topic><topic>Heuristic</topic><topic>heuristics</topic><topic>Manufacturing cells</topic><topic>Mathematical models</topic><topic>mixed integer linear programming</topic><topic>Optimization</topic><topic>Production scheduling</topic><topic>Scheduling</topic><topic>Splitting</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Süer, Gürsel A.</creatorcontrib><creatorcontrib>Ates, Ozan K.</creatorcontrib><creatorcontrib>Mese, Emre M.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering 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>International journal of production research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Süer, Gürsel A.</au><au>Ates, Ozan K.</au><au>Mese, Emre M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness</atitle><jtitle>International journal of production research</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>52</volume><issue>19</issue><spage>5656</spage><epage>5674</epage><pages>5656-5674</pages><issn>0020-7543</issn><eissn>1366-588X</eissn><abstract>This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. 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| source | Taylor & Francis; Business Source Complete |
| subjects | cell scheduling Due dates Genetic algorithms group scheduling Heuristic heuristics Manufacturing cells Mathematical models mixed integer linear programming Optimization Production scheduling Scheduling Splitting Studies |
| title | Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness |
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