Mathematical Modelling In Logistics Transportation Problems with The Direct Search


  • Silvi Anggraini Rahman Graduate school of Mathematics, Universitas Sumatera Utara
  • Herman Mawengkang Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia
  • Sutarman Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia




Modelling, Logistic problems, Integer Programming, Direct search


Migration of rural communities to cities increases logistics activities in urban areas to meet customer needs because there is a close relationship between economic expansion and usage. Daily fluctuating demand for logistics, uncertain driving times and insufficient parking spaces are some of the factors that link the crisis in urban logistics in urban areas, which directly affects operational costs, the environment and its success or failure. The related steps of modeling optimization have a major impact in making complex transportation and logistics systems competitive with each other. This paper proposes a model optimization to solve transportation problems mathematically. The integer programming model would be suitable for the problems that have been described. the author uses direct search to complete the model.


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Author Biographies

Herman Mawengkang, Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia



Sutarman, Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia





Abdulkarim, H. A., & Alshammari, I. F. (2015). Comparison of algorithms for solving traveling salesman problem. International Journal of Engineering and Advanced Technology, 4(6), 76–79.

Anderson, D. L., Britt, F. F., & Favre, D. J. (2007). The 7 principles of supply chain management. Supply Chain Management Review, 11(3), 41–46.

Bräysy, O., Dullaert, W., & Nakari, P. (2009). The potential of optimization in communal routing problems: case studies from Finland. Journal of Transport Geography, 17(6), 484–490.

Das, S., & Bhattacharyya, B. K. (2015). Optimization of municipal solid waste collection and transportation routes. Waste Management, 43, 9–18.

Ghiani, G., Laporte, G., & Musmanno, R. (2013). Introduction to Logistics Systems Management. In Introduction to Logistics Systems Management.

Hayes, R. H., & Wheelwright, S. C. (1985). Restoring our Competitive Edge: Competing Through Manufacturing. John Wiley & Sons.

Hübner, A. H., Kuhn, H., & Sternbeck, M. G. (2013). Demand and supply chain planning in grocery retail: an operations planning framework. International Journal of Retail & Distribution Management.

Ivanov, D., Tsipoulanidis, A., & Schönberger, J. (2021). Global supply chain and operations management. Springer.

Jünger, M., Reinelt, G., & Rinaldi, G. (1995). The traveling salesman problem. Handbooks in Operations Research and Management Science, 7, 225–330.

Kallehauge, B., Larsen, J., Madsen, O. B. G., & Solomon, M. M. (2005). Vehicle routing problem with time windows. Springer.

Kim, B.-I., Kim, S., & Sahoo, S. (2006). Waste collection vehicle routing problem with time windows. Computers & Operations Research, 33(12), 3624–3642.

Kim, G., Ong, Y.-S., Heng, C. K., Tan, P. S., & Zhang, N. A. (2015). City vehicle routing problem (city VRP): A review. IEEE Transactions on Intelligent Transportation Systems, 16(4), 1654–1666.

Korte, B. H., Vygen, J., Korte, B., & Vygen, J. (2011). Combinatorial optimization (Vol. 1). Springer.

Krause, D., Youngdahl, W., & Ramaswamy, K. (2014). Manufacturing - Still a missing link? In Journal of Operations Management.

Mazyavkina, N., Sviridov, S., Ivanov, S., & Burnaev, E. (2021). Reinforcement learning for combinatorial optimization: A survey. Computers & Operations Research, 134, 105400.

Pilati, F., & Tronconi, R. (2023). Multi-objective optimisation for sustainable few-to-many pickup and delivery vehicle routing problem. International Journal of Production Research, 1–30.

Roberts, T. L. (2007). Right product, right rate, right time and right place… the foundation of best management practices for fertilizer. Fertilizer Best Management Practices, 29, 1–8.

Taylor, F. W. (2023). the Rise of Scientific Management. The Quantified Worker: Law and Technology in the Modern Workplace, 9.

Toth, P., & Vigo, D. (2002). An overview of vehicle routing problems. The Vehicle Routing Problem, 1–26.

Trentesaux, D. (2009). Distributed control of production systems. Engineering Applications of Artificial Intelligence, 22(7), 971–978.

Weigel, D., & Cao, B. (1999). Applying GIS and OR techniques to solve Sears technician-dispatching and home delivery problems. Interfaces, 29(1), 112–130.


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How to Cite

Rahman, S. A., Mawengkang, H. ., & Sutarman, S. (2023). Mathematical Modelling In Logistics Transportation Problems with The Direct Search. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(3), 1528-1535.

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