A Multi-Objective Model for Location-Allocation Problem in a Supply Chain

Mokhtari Karchegani, F.; Shirouyehzad, H.; Tavakkoli-Moghaddam, R.

doi:10.22105/riej.2017.49155

Document Type : Research Paper

Authors

¹ Department of Human Science, Management group, Najafabad Branch, Islamic Azad University, Najafabad, Iran

² Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

³ School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

10.22105/riej.2017.49155

Abstract

The fast changing and dynamic global business environment require companies to plan their entire supply chain from the raw material supplier to the end customer. In this paper, we design an integrated supply chain including multiple suppliers, multiple factories, multiple distributors, multiple customers, multiple products, and multiple transportation alternatives. A new multi-objective mixed-integer nonlinear programming model is proposed to deal with this facility location-allocation problem. It considers two conflicting objectives simultaneously, and then the problem is transformed into a multi-objective linear one. The first objective function aims to minimize total losses of the supply chain including raw material purchasing costs, transportation costs and establishment costs of factories and distributions. The second objective function is to minimize the sum deterioration rate of end products and raw materials incurred by transportation alternatives. Finally, the proposed model is solved as a single-objective, mixed-integer, programming model applying the Global Criteria Method. We test their model with numerical example and the results indicate that the proposed model can provide a promising approach to fulfill customer demand and design an efficient supply chain.

Keywords

Main Subjects

Supply chain management

References

[1] Mirzapour Al-e-hashem, S.M.J. and Malekly, H. and Aryanezhad, M.B.(2011). A multi-objective robust optimization model for multi-product multi-site aggregate

production planning in a supply chain under uncertainty. International Journal of Production Economics. Vol. 134, No.1, pp. 28–42.

[2] Gebennini, E. and Gamberini, R. and Manzini, R. (2009). An integrated production– distribution model for the dynamic location and allocation problem with safety stock optimization. International Journal of Production Economics. Vol. 122, No.1, pp. 286–304.

[3] Drezner, Z.( 1995). Dynamic facility location: The progressive p-median problem. International Journal of Location Science. Vol. 3, No. 1, pp. 1–7.

[4] Cooper, L.( 1963). Location-Allocation Problems.Operations Research. Vol. 11, No. 3, pp. 331-343.

[5] Manzini R. and Gebenninib E., (2008). Optimization models for the dynamic facility location and allocation problem. International Journal of Production Research. Vol. 46, No. 8, pp. 4543-4571.

[6] Torres-Sotoa J. E. and Üstera Halit, (2011). Dynamic-demand capacitated facility location problems with and without relocation. International Journal of Production Research.Vol.49, No.13, pp.3979-4005.

[7] Bhaskaran, S. and Turnquist, M.A., (1990). Multiobjective transportation considerations in multiple facility location. Transportation Research Part A: General.Vol. 24, No. 2, pp.139–148.

[8] Rosing, K.E., (1992). An optimal method for solving the (generalized) multi-Weber problem. European Journal of Operational. Vol. 58, No. 3, pp. 414–426.

[9] Jiang, J.-L., Yuan, X.M., (2008). A heuristic algorithm for constrained multi-source Weber problem – The variational inequality approach. European Journal of Operational Research.Vol. 187, No. 2, pp. 357–370.

[10] Dogan, K. and Goetschalckx, M., (1999). A primal decomposition method for the integrated design of multi-period production–distribution systems. IIE Transactions. Vol.31, No. 11, pp. 1027-1036.

[11] Jayaraman, V. and Pirkul, H., (2001). Planning and coordination of production and distribution facilities for multiple commodities. European Journal of Operational Research.Vol. 133, No.2, pp. 394–408.

[12] Kanyalkar A.P. and Adil G.K., (2005). An integrated aggregate and detailed planning in a multisite production environment using linear programming. International Journal of Production Research.Vol. 43, No.20, pp. 4431-4454.

[13] Amiri, A., (2006). Designing a distribution network in a supply chain system: Formulation and efficient solution procedure. European Journal of Operational Research. Vol.171, No.2, pp. 567–576.

[14] Chen, C.-W. and Sha, D.Y., (2005). Heuristic approach for solving the multi- objective facility layout problem. International Journal of Production Research. Vol. 43, No.21, pp. 4493-4507.

[15] Singh S.P. and Singh V.K., (2011). Three-level AHP-based heuristic approach for a multi objective facility layout problem. International Journal of Production Research.Vol. 49, No.4, pp. 1105-1125.

[16] Navidi H., Bashiri M. and Messi M., (2011). A heuristic approach on the facility layout problem based on game theory. International Journal of Production Research. Vol. 50, No. 6, pp. 1512-1527.

[17] Jolai F., Tavakkoli-Moghaddam R. and Taghipour M., (2011). A multi- objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup.drop-off locations. International Journal of Production Research. Vol. 50, No. 15, pp. 4279-4293.

[18] Drezner, Z. and Hamacher, H.W., (2002). Facility Location: Applications and Theory. 1st edition, Springer, New York, pp. 329-369.

[19] Klose, A. and Drexl, A., (2005). Facility location models for distribution system design. European Journal of Operational Research. Vol. 162, No.1, pp. 4–29.

[20] Melo M.T., Nickel S. and Saldanha-da-Gama F., (2009). Facility location and supply chain management – A review. European Journal of Operational Research. Vol.196, No.2, pp. 401-412.

[21] Farahani R.Z., SteadieSeifi M. and Asgari N., (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling. Vol. 34, No.7, pp. 1689-1709.

[22] Nikolopoulou A. and G. Ierapetritou M., (2012). Hybrid simulation based optimization approach for supply chain management. Computers & Chemical Engineering. Vol. 47, Mo. 20, pp. 183–193.

[23] Cóccolaa M.E. and Zamarripab M. and Méndeza C.A. and Espu˜nab A., (2013). Toward integrated production and distribution management in multi-echelon supply chains. Computers & Chemical Engineering. Vol.57, No. 15, pp. 78–94.

[24] Tancrez J.S. and Lange J.C and Semal P., (2012). A location-inventory model for large three-level supply chains. Transportation Research Part E: Logistics and Transportation Review. Vol. 48, No. 2, pp. 485–502.

[25] Schütz P.and Stougie L.and Tomasgard A., (2008). Stochastic facility location with general long-run costs and convex short-run costs. Computers and Operations Research. Vol. 35, No.9, pp. 2988 – 3000.

[26] Sowmya Danalakshmi C. and Mohan Kumar G. and Gopalan M., (2012). Minimisation of the total operating cost by using supply chain optimisation model (COSCOM). International Journal of Logistics Economics and Globalisation. Vol. 4, No. 1, pp. 76-98.

[27] Zeinal Hamadani A. and Abouei Ardakan M. and Rezvan T. and Honarmandian M., (2013). Location-allocation problem for intra-transportation system in a big company by using meta-heuristic algorithm. Socio-Economic Planning Sciences. Vol 47, No.4, pp. 309–317.

[28] Arabatzis G. and Petridi K. and Galatsidas S. and Ioannou K., (2013). A demand scenario based fuelwood supply chain: A conceptual model. Renewable and Sustainable Energy Reviews. Vol. 25, pp. 687–697.

[29] De-León Almaraz S. and Azzaro-Pantel C. and Montastruc L. and Pibouleau

L. and Baez Senties O., (2013). Assessment of mono and multi-objective optimization to design a hydrogen supply chain. International Journal of Hydrogen Energy. Vol. 38, No. 33, pp. 14121–14145.

[30] Ambrosino D. and Scutellà M.G., (2005). Distribution network design: New problems and related models. European Journal of Operational Research. Vol. 165, No.3, pp. 610–624.

[31] Barros A.I. and Dekker R. Scholten V. (1998). A two-level network for recycling sand: A case study. European Journal of Operational Research. Vol. 110, No.2, pp.199–214.

[32] Canel C. and Khumawala B.M. and Law J. and Loh A., (2001). An algorithm for the capacitated, multi-commodity multi-period facility location problem. Computers and Operations Research. An algorithm for the capacitated, multi- commodity multi-period facility location problem, Vol. 28, No.5, pp. 411–427.

[33] Cordeau J.F. and Pasin F. and Solomon M.M., (2006). An integrated model for logistics network design. Annals of Operations Research. Vol. 144, No.1, pp. 59– 82.

[34] Eskigun E. and Uzsoy R. and Preckel P.V. and Beaujon G. and Krishnan S. and Tew J.D., (2005). Outbound supply chain network design with mode selection, lead times and capacitated vehicle distribution centers. European Journal of Operational Research. Vol. 165, No.1, pp.182–206.

[35] Gunnarsson H. and Rnnqvist M. and Lundgren J.T., (2004). Supply chain modelling of forest fuel. European Journal of Operational Research. Vol.158, No.1, pp.103–123.

[36] Lee D.-H. and Dong M., (2008). A heuristic approach to logistics network design for endof- lease computer products recovery. Transportation Research Part E: Logistics and Transportation Review. Vol.44, No.3, pp. 455–474.

[37] Melo M.T. and Nickel S. and Saldanha-da-Gama F., (2006). Dynamic multi- commodity capacitated facility location: A mathematical modeling framework for strategic supply chain planning. Computers and Operations Research. Vol.33, No.1, pp.181–208.

[38] Vila D. and Martel A. and Beauregard R., (2006). Designing logistics networks in divergent process industries: A methodology and its application to the lumber industry. International Journal of Production Economics. Vol.102, No.2, pp. 358–378

International Journal of Research in Industrial Engineering

A Multi-Objective Model for Location-Allocation Problem in a Supply Chain

References

References

Volume 4, 1(4)
November 2015
Pages 24-42

A Multi-Objective Model for Location-Allocation Problem in a Supply Chain

References

References

Volume 4, 1(4)November 2015Pages 24-42

Volume 4, 1(4)
November 2015
Pages 24-42