Facility layout using weighted association rule-based data mining algorithms: Evaluation with simulation

• Published in: Expert systems with applications 2012, Vol.39 (1), p.3-13
• Main Authors: Altuntas, Serkan, Selim, Hasan
• Format: Article
• Language: English
• Subjects: Algorithms; Computer simulation; Criteria; Data mining; Expert systems; Facility layout; Marketing; Materials handling; Productivity; Simulation; Weighted association rule
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2011.06.045

► We propose new weighted association rule-based data mining approaches for facility layout problem. ► The approaches are compared in terms of general performance criteria for the facility layout problems using simulation. ► “Demand”, “part handling factor” and “efficiency of material handling equipment” are used as the weighting criteria. Facility layout has considerable effects on the operational productivity and efficiency of a facility because of its direct effect on material handling costs. The objective of this study is to propose new weighted association rule-based data mining approaches for facility layout problem. Classic association rule-based approaches assume that each item has the same level of significance. On the other hand, in weighted association rule-based approaches, each item is assigned a weight according to its significance with respect to some user defined criteria. In this study, different weighted association rule-based data mining approaches, namely MINWAL(O), MINWAL(W), WARM and BWARM, are applied to facility layout problem. To confirm the viability of the proposed approaches, two case studies are presented. The approaches are compared in terms of general performance criteria for the facility layout problems using simulation. This is the first study that applies weighted association rule-based data mining approaches to facility layout problem. To address the needs in practice, “demand”, “part handling factor” and “efficiency of material handling equipment” are used as the weighting criteria. Then, this study differs from the previous works in that it considers the three key location factors together.