The optimal decision of customer order decoupling point for order insertion scheduling in logistics service supply chain

Customer demand for order insertions impacts the position of the customer order decoupling point (CODP) in a logistics service supply chain (LSSC). This paper focuses on how the parameters of inserted orders affect the position of the CODP when a logistics service integrator (LSI) is operating a mass customization logistics service. Considering customer demand for orders to be inserted, a CODP decision model for LSSCs is developed based on a two-echelon LSSC consisting of an LSI and several customers. The objectives of the model are to maximize the profit and to ensure the comprehensive satisfaction of the LSI. Conducting numerical analyses on a specific dataset, it was discovered that the scale effect coefficient and service volume of the inserted order have a clear influence on the CODP decision, while the order variation coefficient does not. Furthermore, the LSI will not accept an inserted order when the inserted order has a high variation coefficient or a low price.

[1]  Fengming M. Chang,et al.  The relationship between affecting factors and mass-customisation level: the case of a pigment company in Taiwan , 2010 .

[2]  Augusto Q. Novais,et al.  A discrete time reactive scheduling model for new order insertion in job shop, make-to-order industries , 2010 .

[3]  Yixiong Feng,et al.  An exploratory study of the general requirement representation model for product configuration in mass customization mode , 2009 .

[4]  Liu Wei-hua,et al.  An emergency order allocation model based on multi‐provider in two‐echelon logistics service supply chain , 2011 .

[5]  Hua Wang,et al.  Defects tracking in mass customisation production using defects tracking matrix combined with principal component analysis , 2013 .

[6]  Liwen Liu,et al.  Optimization analysis of supply chain scheduling in mass customization , 2009 .

[7]  Chris N. Potts,et al.  Rescheduling for New Orders , 2004, Oper. Res..

[8]  Daijian Tang,et al.  Postponement Method in Service Process Re-Engineering: A Catering Case , 2010, 2010 International Conference on Management and Service Science.

[9]  M. Christopher,et al.  Measuring agile capabilities in the supply chain , 2001 .

[10]  William L. Berry,et al.  Linking Systems to Strategy , 1992 .

[11]  Han Hoogeveen,et al.  Rescheduling for new orders on a single machine with setup times , 2012, Eur. J. Oper. Res..

[12]  Joakim Wikner,et al.  Mass customization in terms of the customer order decoupling point , 2004 .

[13]  Zhonghua Wu,et al.  Mathematical Modeling of Heat and Mass Transfer in Energy Science and Engineering , 2013 .

[14]  V. Donk.  Make to stock or make to order: the decoupling point in the food processing industries , 2001 .

[15]  Pmj Paul Giesberts,et al.  Dynamics of the customer order decoupling point: impact on information systems for production control , 1992 .

[16]  Linda D. Peters,et al.  IT and the mass customization of services: the challenge of implementation , 2000, Int. J. Inf. Manag..

[17]  Weihua Liu,et al.  A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service , 2012 .

[18]  Patrik Jonsson,et al.  Improving performance with sophisticated master production scheduling , 2015 .

[19]  Mohsen Jafari Songhori,et al.  An integrated fuzzy group decision making/fuzzy linear programming (FGDMLP) framework for supplier evaluation and order allocation , 2009 .

[20]  Paolo Toth,et al.  Scheduling extra freight trains on railway networks , 2010 .

[21]  Dominique M. Hanssens,et al.  Market Response Models: Econometric and Time Series Analysis , 1989 .

[22]  Yuming Mo,et al.  Order Allocation Research of Logistics Service Supply Chain with Mass Customization Logistics Service , 2013 .

[23]  Yi Yang,et al.  Decision model of customer order decoupling point on multiple customer demands in logistics service supply chain , 2014 .

[24]  Daijian Tang,et al.  Identification of postponement point in service delivery process: A description model , 2009, 2009 6th International Conference on Service Systems and Service Management.

[25]  Alan Harrison,et al.  Implications of form postponement to manufacturing a customized product , 2006 .

[26]  Rubén Ruiz,et al.  TWO NEW ROBUST GENETIC ALGORITHMS FOR THE FLOWSHOP SCHEDULING PROBLEM , 2006 .

[27]  Irene C. L. Ng,et al.  Contextual variety, Internet-of-Things and the choice of tailoring over platform: Mass customisation strategy in supply chain management $ , 2015 .

[28]  Yanhong Qin,et al.  On Delaying CODP to Distribution Center in Mass Customization , 2011, CSIE 2011.

[29]  Jeffrey E. Schaller.  Single machine scheduling with early and quadratic tardy penalties , 2004, Comput. Ind. Eng..

[30]  João Carlos Lourenço,et al.  A multicriteria model for assigning new orders to service suppliers , 2002, Eur. J. Oper. Res..

[31]  D. Wittink,et al.  Building Models for Marketing Decisions , 2000 .

[32]  Donghe Pei,et al.  Cusps of Bishop Spherical Indicatrixes and Their Visualizations , 2013 .

[33]  Amos H. C. Ng,et al.  Dynamic implications of customer order decoupling point positioning , 2011 .

[34]  Steven Hamblin,et al.  On the practical usage of genetic algorithms in ecology and evolution , 2013 .

[35]  Ji Jian-hua,et al.  Study on CODP Position of Process Industry Implemented Mass Customization , 2007 .

[36]  Chris N. Potts,et al.  Rescheduling for Multiple New Orders , 2007, INFORMS J. Comput..

[37]  C. Chandra,et al.  Managing logistics for mass customization: the new production frontier , 2004, Proceedings World Automation Congress, 2004..

[38]  Jan Olhager,et al.  Strategic positioning of the order penetration point , 2003 .

[39]  Yves Dallery,et al.  Optimising reorder intervals and order-up-to levels in guaranteed service supply chains , 2014 .

[40]  Bernard De Baets,et al.  An ideal point method for the design of compromise experiments to simultaneously estimate the parameters of rival mathematical models , 2010 .

[41]  Jean-Marie Proth,et al.  The one machine scheduling problem: Insertion of a job under the real-time constraint , 2009, Eur. J. Oper. Res..

[42]  Jan Olhager,et al.  Long-term capacity management: Linking the perspectives from manufacturing strategy and sales and operations planning , 2001 .

[43]  Yong-Wu Zhou,et al.  Supply Chain Coordination for Newsvendor-Type Products with Two Ordering Opportunities , 2011 .

[44]  Christopher S. Tang,et al.  Modelling the Costs and Benefits of Delayed Product Differentiation , 1997 .

[45]  Chung-Lun Li,et al.  Managing uncertainty in logistics service supply chain , 2007 .

[46]  Ming Dong,et al.  A dynamic constraint satisfaction approach for configuring structural products under mass customization , 2012, Eng. Appl. Artif. Intell..

[47]  Hongzhi Liu,et al.  Logistics service process re-engineering for mass customization , 2005, Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005..

[48]  Masoud Rabbani,et al.  Order partitioning and Order Penetration Point location in hybrid Make-To-Stock/Make-To-Order production contexts , 2011, Comput. Ind. Eng..

[49]  Giovani J.C. da Silveira,et al.  The mass customization decade: An updated review of the literature , 2012 .

[50]  Xiaohua Liu,et al.  Three-dimensional model of customer order decoupling point position in mass customisation , 2010 .

[51]  Joakim Wikner,et al.  Integrating production and engineering perspectives on the customer order decoupling point , 2005 .

[52]  Bibo Yang,et al.  Single machine rescheduling with new jobs arrivals and processing time compression , 2007 .

[53]  Reha Uzsoy,et al.  Predictable scheduling of a single machine with breakdowns and sensitive jobs , 1999 .

[54]  Susmita Bandyopadhyay,et al.  Solving a tri-objective supply chain problem with modified NSGA-II algorithm , 2014 .