You are here

Home » Content

Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem

Journal Name:

  • Journal of Industrial Engineering and Management

Publication Year:

  • 2013

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk.Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system allows an easier generation of many different alternatives for the supply network configuration.
Bookmark/Search this post with
FULL TEXT (PDF): 
PDF icon arastrmx_141136_6_pp_779-795.pdf
  • 3
779-795
  • English

REFERENCES

References: 

Alvarez, E. (2007). Multi-plant production scheduling in SMEs. Robotics and ComputerIntegrated Manufacturing, 23, 608-613. http://dx.doi.org/10.1016/j.rcim.2007.02.006
Chern, C.C. & Yang, I.C. (2011). A heuristic master planning algorithm for supply chains that
consider substitutions and commonalities. Expert Systems with Applications, 38,
14918-14934. http://dx.doi.org/10.1016/j.eswa.2011.05.055
Eisemann, K. (1957). The trim problem. Management Science, 3, 279-284.
http://dx.doi.org/10.1287/mnsc.3.3.279
Garcia-Sabater, J.P., Maheut, J., & Marin-Garcia, J.A. (2013). A new formulation technique to
model Materials and Operations Planning: the Generic Materials and Operations Planning
(GMOP) Problem. European J.Industrial Engineering, 7, In Press.
Goetschalckx, M., Vidal, C.J., & Dogan, K. (2002). Modeling and design of global logistics
systems: A review of integrated strategic and tactical models and design algorithms. European
Journal of Operational Research, 143, 1-18. http://dx.doi.org/10.1016/S0377-2217(02)00142-X
Graves, S.C. & Willems, S.P. (2005). Optimizing the supply chain configuration for new
products. Management Science, 51, 1165-1180. http://dx.doi.org/10.1287/mnsc.1050.0367
Lang, J.C. (2009). Production and inventory management with substitutions. (Lecture Notes in
economics and mathematical systems ed.) (Vol. 636) Berlin: Springer.
Li, H., & Womer, K. (2008). Modeling the supply chain configuration problem with resource
constraints. International Journal of Project Management, 26, 646-654.
http://dx.doi.org/10.1016/j.ijproman.2007.08.004
Lloret, J., Garcia-Sabater, J.P., & Marin-Garcia, J. (2008). Cooperative Multisite Production Rescheduling. In Y. Luo (ed.), Cooperative design, visualization, and engineering (5220 ed.,
156-163). Springer-Verlag Berlin Heidelberg.
Maheut, J. & Garcia-Sabater, J.P. (2011). La Matriz de Operaciones y Materiales y la Matriz de
Operaciones y Recursos, un nuevo enfoque para resolver el problema GMOP basado en el
concepto del Stroke. Dirección y Organización, 45, 46-57.
http://www.revistadyo.com/index.php/dyo/article/viewFile/382/402
Maheut, J., Garcia-Sabater, J.P., & Mula, J. (2012). A supply Chain Operations Lot-Sizing and
Scheduling Model with Alternative Operations. In S.P. Sethi, M. Bogataj & L. Ros-McDonnell
(eds.), Industrial Engineering: Innovative Networks, 5th International Conference on
Industrial Engineering and Industrial Management "CIO 2011", Cartagena, Spain, September
2011, Proceedings (pp. 309-316). London: Springer-Verlag London.
Mohammadi Bidhandi, H., Yusuff, R., Megat Ahmad, M.M.H., & Abu Bakar, M.R. (2009).
Development of a new approach for deterministic supply chain network design. European
Journal of Operational Research, 198, 121-128. http://dx.doi.org/10.1016/j.ejor.2008.07.034
Mula, J., Maheut, J., & Garcia-Sabater, J.P. (2011). Mathematical Modelling for Supply Chain
Configuration. In Mathematical Modelling (pp. 1-17). Nova Science Publishers, Inc.
Nagurney, A. (2010). Optimal supply chain network design and redesign at minimal total cost
and with demand satisfaction. International Journal of Production Economics, 128, 200-208.
http://dx.doi.org/10.1016/j.ijpe.2010.07.020
Sahling, F., Buschkühl, L., Tempelmeier, H., & Helber, S. (2009). Solving a multi-level
capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize
heuristic. Computers & Operations Research, 36, 2546-2553.
http://dx.doi.org/10.1016/j.cor.2008.10.009
Saiz, E., & Castellano, E. (2008). Driving Mass Customisation In Supply Networks. A Machine
Tool Sector Case Study. In Joint Conference of the International Mass Customization Meeting
2008 (IMCM'08) and the International Conference on Economic, Technical and Organisational
Aspects of Product Configuration Systems (PETO'08).
Salvador, F., Rungtusanatham, M., & Forza, C. (2004). Supply-chain configurations for mass
customization. Production Planning and Control, 15, 381-397.
http://dx.doi.org/10.1080/0953728042000238818
Seeanner, F., & Meyr, H. (2012). Multi-stage simultaneous lot-sizing and scheduling for flow
line production. OR Spectrum. In press, 1-41.
Stadtler, H. (2005). Supply chain management and advanced planning--basics, overview and
challenges. European Journal of Operational Research, 163, 575-588.
http://dx.doi.org/10.1016/j.ejor.2004.03.001
Vidal-Carreras, P.I., Garcia-Sabater, J.P., & Coronado-Hernandez, J.R. (2012). Economic lot
scheduling with deliberated and controlled coproduction. European Journal of Operational
Research, 219, 396-404. http://dx.doi.org/10.1016/j.ejor.2011.12.020
Wang, G., Huang, S.H., & Dismukes, J.P. (2004). Product-driven supply chain selection using
integrated multi-criteria decision-making methodology. International Journal of Production
Economics, 91, 1-15. http://dx.doi.org/10.1016/S0925-5273(03)00221-4
Xiaoyan, Z., & Wilhelm, W.E. (2006). Scheduling and lot sizing with sequence-dependent
setup: A literature review. IIE Transactions, 38, 987-1007.
http://dx.doi.org/10.1080/07408170600559706

Thank you for copying data from http://www.arastirmax.com