Browse > Article

A Framework of the Integrated Production/Distribution Model with Non-Integer Lags  

Kim, Jong Soo (Department of Industrial Engineering, Hanyang University)
Shin, Ki Young (Department of Industrial Engineering, Hanyang University)
Moon, Chi Ung (Department of Industrial Engineering, Hanyang University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.31, no.2, 2005 , pp. 120-126 More about this Journal
Abstract
Until now, the traditional production models and logistics have developed a broader strategic approach called supply chain. However, there are some obstacles to apply industry practice because of unrealistic assumptions. The most serious of them is that they assume the lead times are integer multiples of the planning time grid. This assumption makes it difficult to express the processing and transportation lags correctly. Thus, in this paper, we propose a new methodology for the integrated production/distribution model having non-integer time lags using the concept of dynamic production function. In case that the time lags are integer or non-integer, the dynamic production function reflects well the situation under given environments. Experiments show that the proposed model can express the real system more accurately than the prior model can.
Keywords
supply chain management; non-integer leadtime; integrated production/distribution model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Cachon, G.,Fisher, M.(2000), Supply Chain Inventory Management and The Value of Shared Information, Management Science, 46, 1032-1048   DOI   ScienceOn
2 ErengGc S, Simpson NC, Vakharia AJ (1999), Integrated production/ distribution planning in supply chains: Aninvited review, European Journal of Operational Research, 115,219-236   DOI   ScienceOn
3 Hackman ST, Leachman RC (1989), A general framework for modeling production, Management Science, 35,478-495   DOI   ScienceOn
4 Dasei A., Verter V. (2001), A Continuous Model for Production Distribution System Design, European Journal of Operational Research, 129,287-298   DOI   ScienceOn
5 Escudero, L.F., Schumann (1999), A Modeling Framework for Supply Chain Management under Uncertainty, European Journalof Operational Research, 119,14-34   DOI   ScienceOn
6 Brooke A, et. al. (1998), GAMS A User's Guide, GAMS Development Corporation
7 Jayaraman, V., Pirkul, R. (2001), Planning and Coordination of Production and Distribution Facilities for Multiple Commodities, European Journal of Operational Research, 133, 394-408   DOI   ScienceOn
8 Lee, R., Padmanabhan, P., Whang, S. (1997), Information Distortion in a Supply Chain: The Bullwhip effect, Management Science, 43,546-558   DOI   ScienceOn
9 Chen, F. et al. (2000), Quantifying the Bullwhip Effect in a Simple Supply Chain: TheImpact of Forecasting, LeadTimes, andInformation, Management Science, 46, 436-443   DOI   ScienceOn