JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Heuristic-Based Algorithm for Production Planning Considering Allocation Rate Conformance to Prevent Unstable Production Chain
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Heuristic-Based Algorithm for Production Planning Considering Allocation Rate Conformance to Prevent Unstable Production Chain
Kim, Taehun; Ji, Bongjun; Cho, Hyunbo;
  PDF(new window)
 Abstract
This study solved the problem of unstable production chains by considering allocation rate conformance. We proposed two phased algorithm suitable for solving production planning that considers allocation rate conformance; the first phase was heuristic initial solution generation, and the second phase was tabu-search based solution improvement. By using three data sets which have different sizes of data and three different criteria, the results of proposed algorithm were compared with MIP results. The proposed algorithm showed the best production plan in terms of allocation rate conformance, and it was appropriate for other criteria; it solved the problem of unstable production chains by solving concentrated and unfair allocation.
 Keywords
Tabu Search;Imbalanced Allocation;Unfair Allocation;Production Contract;
 Language
English
 Cited by
1.
Sequencing the Mixed Model Assembly Line with Multiple Stations to Minimize the Total Utility Work and Idle Time, Industrial Engineering and Management Systems, 2016, 15, 1, 1  crossref(new windwow)
 References
1.
Cachon, G. P. (2003), Supply chain coordination with contracts, Handbooks in Operations Research and Management Science, 11, 229-340.

2.
Chen, Y. Y. (2010), An Analytical Framework for Multi-Site Supply Chain Planning Problems, World Academy of Science, Engineering and Technology, 41, 1135-1141.

3.
Ehrgott, M. (2005), Multicriteria optimization, Springer.

4.
Gelders, L. F. and Wassenhove, L. N. V. (1981), Production planning: a review, European Journal of Operational Research, 7(2), 101-110. crossref(new window)

5.
Glover, F. (1990), Tabu search: A tutorial, Interfaces, 20(4), 74-94. crossref(new window)

6.
Hwang, C. L. and Masud, A. S. M. (1979), Multiple objective decision making-methods and applications: a state-of-the-art survey, Springer, Berlin.

7.
Kibira, Deogratias, et al. (2015), Analysis of Standards Towards Simulation-Based Integrated Production Planning, Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, Springer International Publishing, 39-48.

8.
Kim, T. et al. (2015), Decomposing Packaged Services Towards Configurable Smart Manufacturing Systems, Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, Springer International Publishing, 74-81.

9.
Lin, J. T. and Chen, Y.Y. (2007), A multi-site supply network planning problem considering variable time buckets-A TFT-LCD industry case, The International Journal of Advanced Manufacturing Technology, 33(9), 1031-1044. crossref(new window)

10.
Moon, C., Kim, J. and Hur, S. (2002), Integrated process planning and scheduling with minimal total tardiness in multi-plants supply chain, Computers and Industrial Engineering, 43, 331-349. crossref(new window)

11.
Roux, W., Dauzere-Peres, S., and Lasserre, J. B. (1999), Planning and scheduling in a multi-site environment, Production Planning and Control, 10, 19-28. crossref(new window)

12.
Timpe, C. H. and Kallrath, J. (2000), Optimal planning in large multi-site production networks, European Journal of Operational Research, 126, 422-435. crossref(new window)

13.
Vercellis, C. (1999), Multi-plant production planning in capacitated self-configuring two-stage serial systems, European Journal of Operational Research, 119, 451-460. crossref(new window)

14.
Wagner, S. M. and Bode, C. (2006), An empirical investigation into supply chain vulnerability, Journal of Purchasing and Supply Management, 12(6), 301-312. crossref(new window)