Marketing Strategies Selection for Supply Chain Management under Uncertainty Propagation

Document Type : Original Article

Author

Faculty member, Shahrood University of technology.

Abstract

In this paper, we consider a closed-loop supply chain supplying products to markets and an after-sales supply chain providing spare parts to fulfill after-sales commitments. Uncertainties of product demand and facility capacity are considered via using continuous probability distribution function and are formulated in the form of a nonlinear mixed integer programming model. In addition, marketing strategies selection for supply chain management and reliable flow creation during the planning periods are considered. Here, we propose a comprehensive mathematical model for determining the best marketing strategies and preserving reliable flow dynamics throughout the chains’ networks. A new memetic algorithm is developed that incorporates genetic algorithm and adaptive variable neighborhood search to find the best solutions. Efficiency of the proposed memetic algorithm is evaluated by comparing its performance with two other solution algorithms. The proposed model and its solution approach are tested using data from an engine production company. We derive some managerial insight by analyzing the correlations among the marketing strategies and how they affect each other.

Keywords

References

1. حسنی، علی‌اکبر؛حسینی، محمدحسن (1394). ارائه یک مدل جامع استوار دوهدفه و الگوریتم ممتیک برای طراحی شبکه زنجیره تأمین برگشتی تحت شرایط عدم‌قطعیت. فصلنامه چشم‌انداز مدیریت صنعتی. 16، 9-32.
2. Bijvank, M., G. Koole, & I.F.A.Vis, (2010). Optimising General Repair Problem with a Service Constraint. European Journal of Operational Research, 204, 76-85.
3. Davies, A., T. Brady, and M. Hobday, (2006). Charting a Path Towards Integrated Solutions. MIT Sloan Management Review, 47, 39-48.
4. Li, G., F.F. Huand, T.C.E. Cheng, & Q. Zheng, (2014). Make-Or-Buy Service Capacity Decision in a Supply Chain Providing After-Sales Service. European Journal of Operational Research, 239, 377-388.
5. Rezapour, S., R. Singh, J.K. Allen, & F. Mistree, (2015). Stochastic Supply Networks Servicing Pre- and After-Sales Markets. in Proceedings of the ASME 2015 International Design Engineering Technical Conferences &Computers and Information in Engineering Conference. Boston, Massachusetts, USA.
6. Gaiardelli, P., N. Saccani, & L. Songini, (2007). Performance Measurement of The After-Sales Service Network - Evidence From The Automotive Industry. Computers in Industry, 58, 698-708.
7. Bacchetti, A. & N. Saccani, (2012). Spare Parts Classification and Demand Forecasting For Stock Control: Investigating The Gap Between Research and Practice. Omega, 40, 722-737.
8. Kosnik, T., M. Wong, D.J. Ji, & K. Hoover, (2006). Outsourcing Vs Insourcing In The Human Resource Supply Chain: A Comparison of The Five Generic Models. Personnel Review, 35(6), 671-684.
9. Kurata, H. & S.H. Nam, (2013). After-Sales Service Competition in a Supply Chain: Does Uncertainty Affect The Conflict Between Profit Maximization and Customer Satisfaction? International Journal of Production Economics, 144, 268-280.
10. Park, M., K.M. Jung, & D.H. Park, (2013). Optimal Post-Warranty Maintenance Policy with Repair Time Threshold For Minimal Repair. Reliability Engineering & System Safety, 111, 147-153.
11. Shahanaghi, k., R. Noorossana, S.G. Jalali-Naini, & M. Heydari, (2013). Failure Modeling and Optimizing Preventive Maintenance Strategy During Two-Dimensional Extended Warranty Contracts. Engineering Failure Analysis, 28, 90–102.
12. Vahdani, H., H. Mahlooji, & A.E. Jahromi, (2013) Warranty Servicing For Discretely Degrading Items with Non-Zero Repair Time Under Renewing Warranty. Computers & Industrial Engineering, 65, 176–185.
13. Wang, W., (2012). A Stochastic Model for Joint Spare Parts Inventory and Planned Maintenance Optimization. European Journal of Operational Research, 216, 127-139.
14. Oner, K.B., G.P. Kiesmuller, & G.J. Van Houtum, (2010). Optimization of Component Reliability in The Design Phase of Capital Goods. European Journal of Operational Research, 205, 615-624.
15. Chien, Y.H. & J.A. Chen, (2008). Optimal Spare Ordering Policy Under a Rebate Warranty. European Journal of Operational Research, 186, 708-719.
16. Chen, X., L. Li, & M. Zhou, (2012). Manufacturer’s Pricing Strategy for Supply Chain with Warranty Period-Dependent Demand. Omega, 40, 807-816.
17. Hartman, J.C. & K. Laksana, (2009). Designing and Pricing Menu of Extended Warranty Contracts. Naval Research Logistics, 56, 199-214.
18. Su, C. & J. Shen, (2012). Analysis of Extended Warranty Policies with Different Repair Options. Engineering Failure Analysis, 25, 49–62.
19. Tsoukalas, M.Z. & G.K. Agrafiotis, (2013). A New Replacement Warranty Policy Indexed By The Product’s Correlated Failure and Usage Time. Computers & Industrial Engineering, 66, 203–211.
20. Zhou, Z., Y. Li, & K. Tang, (2009). Dynamic Pricing and Warranty Policies for Products with Fixed Lifetime. European Journal of Operational Research, 196, 940–948.
21. Gupta, S. & D.R. Lehmann, (2007). Managing Customers As Investments: The Strategic Value of Customers in The Long Run. Pearson Education as Wharton School Publishing, Upper Saddle Reviser: NJ.
22. Barabadi, A., J. Barabady, & T. Markeset, (2014). Application of Reliability Models with Covariates in Spare Part Prediction and Optimization – A Case Study. Reliability Engineering and System Safety, 123, 1-7.
23. Wu, C.H., (2012). Price and Service Competition Between New and Remanufactured Products in a Two-Echelon Supply Chain. International Journal of Production Economics, 140, 496-507.
24. Kurata, H. & S.H. Nam, (2010). After-Sales Service Competition In A Supply Chain: Optimization of Customer Satisfaction Level or Profit Or Both? International Journal of Production Economics, 127, 136-146.
25. Khajavi, S.H., J. Partanen, & J. Holmstron, (2013). Additive Manufacturing In The Spare Parts Supply Chain. Computers in Industry, 65(1), 50-63.
26. Eskandarpour, M., E. Nikbakhsh, & S.H. Zegordi, (2014). Variable Neighborhood Search For The Bi-Objective Post-Sales Network Design Problem: A Fitness Landscape Analysis Approach. Computers & Operations Research, 52, 300–314.
27. Eskandarpour, M., S.H. Zegordi, & E. Nikbakhsh, (2013). A Parallel Variable Neighborhood Search for The Multi-Objective Sustainable Post-Sales Network Design Problem. International Journal of Production Economics, 145(1), 117–131.
28. Faridimehr, S. & S.T.A. Niaki, (2012). A Note On Optimal Price, Warranty Length and Production Rate for Free Replacement Policy in Static Demand Markets. Omega, 40, 805-806.
29. Lieckens, K.T., P.J. Colen, & M.R. Lambrecht, (2013). Optimization of a Stochastic Remanufacturing Network with an Exchange Option. Decision Support Systems, 54, 1548-1557.
30. Rappold, J. & B.D.V. Roo, (2009). Designing Multi-Echelon Service Parts Networks with Finite Repair Capacity. European Journal of Operational Research, 199, 781-792.
31. Sahba, P. & B. Balcioglu, (2011). The Impact of Transportation Delays on Repairshop Capacity Pooling and Spare Part Inventories. European journal of Operational Research, 214, 674-682.
32. Wu, C.C., C.Y. Chou, & C. Huang, (2009). Optimal Price, Warranty Length and Production Rate for Free Replacement Policy in The Static Demand Market. Omega, 37, 29- 39.
33. Rao, B.M., (2011). A Decision Support Model For Warranty Servicing of Repairable Items. Computers and Operations Research, 38, 112–130.
34. Sana, S.S., (2010). An Economic Production Lot Size Model in an Imperfect Production System. European Journal of Operational Research, 201, 158-170.
35. Bernstein, F. & A. Federgruen, (2004). A General Equilibrium Model For Industries With Price and Service Competition. Operations Research, 52(6), 868-886.
Journal of Industrial Management Perspective
Volume 5, Issue 2 - Serial Number 18
September 2015
Pages 33-62

Files

Share

How to cite

Statistics