A fuzzy EOQ model with backorders and forgetting effect on fuzzy parameters: An empirical study

This paper considers a fuzzy lot-sizing problem with forgetting effect.A new fuzzy EOQ model with backorders and forgetting is developed.The result suggests decreasing the maximum inventory and the total inventory cost. The study of learning effect on inventory models with imprecise parameters is a research topic that has recently emerged. The research papers have published so far studied this aspect from a theoretical point of view and thus the literature lacks the investigation of this topic from a practical standpoint. To close this research gap, we conducted a semi-structured interview with a number of industry experts to gain insights into the prevalence of learning and forgetting in real applications. Based on the insights gained from the interviews, we have developed a recently published model by countering the assumption of full transfer of learning. The model developed herein proposes a situation where the knowledge gained by the operator in setting imprecise parameters deteriorates over the planning cycles due to intermittent planning process. A numerical study suggests that accounting for the effect of knowledge depreciation/forgetting on imprecise parameters leads to reduction in maximum inventory, which consequently reduces the total cost of the system.

[1]  R. W. Grubbström,et al.  A century of evolution from Harris׳s basic lot size model: Survey and research agenda , 2014 .

[2]  Shib Sankar Sana,et al.  Backlogging EOQ model for promotional effort and selling price sensitive demand- an intuitionistic fuzzy approach , 2015, Ann. Oper. Res..

[3]  Eleonora Bottani,et al.  A fuzzy lot-sizing problem with two-stage composite human learning , 2016 .

[4]  K. S. Park,et al.  Fuzzy-set theoretic interpretation of economic order quantity , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Christoph H. Glock,et al.  The effect of worker learning on manual order picking processes , 2015 .

[6]  Eric H. Grosse,et al.  Applying fuzzy multi-objective linear programming to a project management decision with nonlinear fuzzy membership functions , 2017, Neural Computing and Applications.

[7]  Shan-Huo Chen,et al.  Backorder Fuzzy Inventory Model under Function Principle , 1996, Inf. Sci..

[8]  P. Drew,et al.  ‘Am I not answering your questions properly?’ Clarification, adequacy and responsiveness in semi-structured telephone and face-to-face interviews , 2013 .

[9]  Flávio Sanson Fogliatto,et al.  Learning curve models and applications: Literature review and research directions , 2011 .

[10]  Lisa S Whiting,et al.  Semi-structured interviews: guidance for novice researchers. , 2008, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[11]  Mohamad Y. Jaber,et al.  An inventory model with backorders with fuzzy parameters and decision variables , 2010, Int. J. Approx. Reason..

[12]  Lily Lin,et al.  APPLYING SIGNED DISTANCE METHOD FOR FUZZY INVENTORY WITHOUT BACKORDER , 2011 .

[13]  Leopoldo Eduardo Cárdenas-Barrón,et al.  Incorporating human learning into a fuzzy EOQ inventory model with backorders , 2015, Comput. Ind. Eng..

[14]  David R. Thomas,et al.  A General Inductive Approach for Analyzing Qualitative Evaluation Data , 2006 .

[15]  Huey-Ming Lee,et al.  Fuzzy Inventory with Backorder for Fuzzy Order Quantity , 1996, Inf. Sci..

[16]  Matthew B. Miles,et al.  Qualitative Data Analysis: An Expanded Sourcebook , 1994 .

[17]  Mohamad Y. Jaber,et al.  A fuzzified version of the economic production quantity (EPQ) model with backorders and rework for a single-stage system , 2014 .

[18]  Hardik N. Soni,et al.  A fuzzy framework for coordinating pricing and inventory policies for deteriorating items under retailer partial trade credit financing , 2013, Comput. Ind. Eng..

[19]  Maurice Bonney,et al.  Economic manufacture quantity (EMQ) model with lot-size dependent learning and forgetting rates , 2007 .

[20]  K. Roulston.  Considering quality in qualitative interviewing , 2010 .

[21]  Nebojsa J. Bojovic,et al.  Fuzzy modeling approach to the rail freight car inventory problem , 2014 .

[22]  Maurice Bonney,et al.  Production breaks and the learning curve: The forgetting phenomenon , 1996 .

[23]  Christoph H. Glock,et al.  An EOQ Model with Fuzzy Demand and Learning in Fuzziness (angenommen) , 2012 .

[24]  B. Crabtree,et al.  The qualitative research interview , 2006, Medical education.

[25]  Leopoldo Eduardo Cárdenas-Barrón,et al.  Celebrating a century of the economic order quantity model in honor of Ford Whitman Harris , 2014 .

[26]  Manoranjan Maiti,et al.  Inventory model with fuzzy lead-time and dynamic demand over finite time horizon using a multi-objective genetic algorithm , 2012, Comput. Math. Appl..

[27]  J. K. Syed,et al.  Fuzzy Inventory Model without Shortages Using Signed Distance Method , 2007 .

[28]  Mohamad Y. Jaber,et al.  Learning Curves : Theory, Models, and Applications , 2011 .

[29]  Manoranjan Maiti,et al.  An EOQ model of deteriorating item in imprecise environment with dynamic deterioration and credit linked demand , 2015 .

[30]  Adrijit Goswami,et al.  Fuzzy EOQ Models for Deteriorating Items with Stock Dependent Demand and Non-Linear Holding Costs , 2009 .

[31]  T. P. Wright,et al.  Factors affecting the cost of airplanes , 1936 .

[32]  Radivoj Petrovic,et al.  EOQ formula when inventory cost is fuzzy , 1996 .

[33]  Raja Ariffin Bin Raja Ghazilla,et al.  Development of a fuzzy economic order quantity model for imperfect quality items using the learning effect on fuzzy parameters , 2015, J. Intell. Fuzzy Syst..

[34]  Kaj-Mikael Björk,et al.  An analytical solution to a fuzzy economic order quantity problem , 2009, Int. J. Approx. Reason..

[35]  Mehran Hojati,et al.  Bridging the gap between probabilistic and fuzzy-parameter EOQ models , 2004 .

[36]  Dilip Kumar Pratihar,et al.  Optimization of variable demand fuzzy economic order quantity inventory models without and with backordering , 2014, Comput. Ind. Eng..

[37]  Christoph H. Glock,et al.  Using qualitative interviewing to examine human factors in warehouse order picking: technical note , 2016 .