Scheduling production and transportation in multi-site supply chain simultaneously regarding to exclusive suppliers

Document Type: Research Paper

Authors

1 Department of Management, University of Isfahan, Isfahan, Iran

2 Department of Industrial Engineering, College of Engineering, Semnan University, Semnan, Iran

3 Department of Industrial Engineering, Islamic Azad University Semnan Branch, Semnan, Iran

Abstract

Delivering on time is an essential factor for the survival of factories in a competitive environment, which requires planning in the supply chain. Therefore, with the correct planning in the supply chain scheduling, it can leads to reduce the cost, lower prices, customer satisfaction and ultimately leads to competitive advantage for organizations. This study considers the scheduling of production and transportation in two-stage Multi-Site supply chain (MS-SC) regarding geographical zoning and using exclusive suppliers (MSZ-SC). The first stage contains suppliers with different production speeds and ability to produce a particular production. The second stage is composed of vehicles, each of which may have a different speed, capacity and setup time. In fact, 5 major factors that are able to be seen as a value for owners are considered. We have presented a mathematical model for scheduling of this supply chain, and then the model coded by Dynamic Genetic Algorithm (DGA), which is an improved version of genetic algorithm, with MATLAB software. Covering the wide range of problems, 648 random problems are solved reaching reasonable achievement. Experimental results from both model with and without zoning, clearly show that proposed model offers better performance in critical variables. In fact, managers are able to use this planning regarding geographical zoning and exclusiveness to gain competitive advantage by time and consequently cost reduction. Better operation abilities in tow-stage proposed model that is clearly shown, certainly, lead to have merits on managerial decision making. 

Keywords

Main Subjects


Amaro, A. C. S., & Barbosa-Póvoa, A. P. F. D. (2008). Planning and scheduling of industrial supply chains with reverse flows: A real pharmaceutical case study. Computers & Chemical Engineering, 32(11), 2606-2625.

Averbakh, I. (2010). On-line integrated production–distribution scheduling problems with capacitated deliveries. European Journal of Operational Research, 200(2), 377-384.

Beheshtinia, M. A., & Khatibi S. A. M. (2017). Analyzing of Three Different Scenarios to Optimize Energy Consumption and Scheduling in Supply Chain. Journal of Energy Management, 7(1), 36-47.

Beheshtinia, M. A., & Moghimi, M. (2015) . Analyzing the Impact of Multi-site Manufacturing on Increasing the Organization Capabilities in Reducing Hazards and Vulnerability of Supply Chain.  Environmental Hazards Management, 2(2), 141-156.

Beheshtinia, M. A. & Moghimi, M. (2017). Injured transportation quality enhancement during natural disaster from the various geographical zones. Human Geography Research Quarterly, 49(3), 539-551.

Cham, H., He, H., Wang, W. (2011). Green Marketing and it’s impact on supply chain management in industry markets. Industrial marketing management journal, 41(4), 557-562.

Chang, Y. & Lee, C. (2004). Machine scheduling with job delivery coordination. European Journal of Operation Research, 158, 470–487.

Chavez, R., Fynes, B., Gimenez, C. & Wlengartem, F. (2012). Accessing the effect of clock speed on the supply chain management practice-performance relationship. Supply chain management: an international journal, 17(3), 235-248.

Chopra, S., Meindl, P. (2010). Supply Chain Management. pp. 41-48 New Jersey: Pearson.

Christopher, M. (2011). Logistics and supply chain Management strategies. 4th Edn., pp. 121-129, FT Prentice Hall, London.

Danese, P., & Romano, P. (2011). Supply chain integration and efficiency performance: a study on the interactions between customer and supplier integration. Supply Chain Management: An International Journal, 16(4), 220-230.

Flynn, B.B., Huo, B. & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58-71.

Forsland, H. & Johnson, P. (2009). Obstacles to supply chain integration of the performance management process in business-supplier: the buyer’s perspective. International journal of operations management, 29(1), 77-95.

Frohlich, M.T., & Westbrook, R. (2001). Arcs of integration: an international study of supply chain strategies.  Journal of Operations Management, 19, 185-200. 

Gimenez, C. & Ventura, E. (2005). Logistics-production, logistics-marketing and external integration: their impact on performance.  International Journal of Operations & Production Management, 25(1), 20-38.

Goldberg, D. E. (1989). Genetic algorithms in search optimization and machine learning. pp. 89-103, MA: Addison-Wesley.

Guo, Z., Yang, J., Leung, S. Y. S., & Shi, L. (2016). A bi-level evolutionary optimization approach for integrated production and transportation scheduling. Applied Soft Computing. Applied Soft Computing, 42(C), 215-228.

Han, B., Zhang, W., Lu, X., & Lin, Y. (2015). On-line supply chain scheduling for single-machine and parallel-machine configurations with a single customer: Minimizing the makespan and delivery cost. European Journal of Operational Research, 244(3), 704-714.

Holland, J. H. (1992). Adaptation in natural and artificial systems. 2th Edn., pp.45-57, University of Michigan press, MIT Press.

Kannan, V.R. & Tan, K.C. (2010). Supply chain integration: cluster analysis of the impact of span of integration. Supply Chain Management: An International Journal, 15(3), 207-215.

Karabuk, S. (2007). Modeling and optimizing transportation decisions in manufacturing supply chain. Transportation Research Part E, 43(4), 321–337.

Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34(2), 346–366.

Lambert, D.M. (2008). An Executive Summary of Supply Chain Management: Processes, Partnerships, Performance. pp. 95-115, Supply Chain Management Institute, Business logistics.

Lee, H.L. (2000). Creating value through supply chain integration. Supply chain management review, 4(4), 30-40.

Lei, L., Lee, K., & Dong, H. (2016). A heuristic for emergency operations scheduling with lead times and tardiness penalties. European Journal of Operational Research, 250(3), 726-736.

Li, H., & Womer, K. (2008). Modeling the supply chain configuration problem with resource constraints. International Journal of Project Management, 26(6), 646-654.

Mehravaran, Y., & Logendran, R. (2012). Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times. International Journal of Production Economics, 135(2), 953-963.

Ritala, P. and Ellonen, H.K. (2010). Competitive advantage in interfirm cooperation: Old and new explanations competitive review. An international Business Journal, 20(5), 367-383.

Rostamian Delavar, M., Hajiaghaei-Keshteli, M., & Molla-Alizadeh-Zavardehi, S. (2010). Genetic algorithms for coordinated scheduling of production and air transportation. Expert Systems with Applications, 37(12), 8255-8266.

Sawik, T. (2014). Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing. Omega, 43, 83-95.

Stein, T.J.S. (1998). Killer Supply Chain. pp. 36-46 Information Week, 708.

Wong, C., Bonoitt, S. & Wong, C.W. (2011). The contingency effects of environmental uncertainty on the relationship between supply chain integration and operational performance.  Journal of operation management, 29, 604-615.

Zandieh, M., & Molla-Alizadeh-Zavardehi, S. (2009). Synchronizing production and air transportation scheduling using mathematical programming models. Journal of Computational and Applied Mathematics, 230(2), 546-558. 

Zegordi, S. H., & Beheshti Nia, M. A. (2009). A multi-population genetic algorithm for transportation scheduling. Transportation Research Part E: Logistics and Transportation Review, 45(6), 946-959.

Zegordi, S. H., Abadi, I. N. K., & Beheshti-Nia, M. A. (2010). A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain. Computers & Industrial Engineering, 58(3), 373-381.

Zhao, X., Baofeng, H., Willem, S., Jeff Hoi, Y.Y. (2011). The impact of internal integration and relationship commitment on external integration. Journal of Operations Management, 29(1-2), 17-32.