Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

Abtahi AR, Bijari A (2017) A noval hybrid meta-heuristic technique applied to the well-known benchmark optimization problems. J Ind Eng Int 13:93–105. doi: 10.1007/s40092-016-0170-x

April J, Glover F, Kelly J, Laguna M (2003) Practical introduction to simulation optimization. In: The 2003 winter simulation conference, New Orleans, LA, pp 71–78

Babazadeh R, Razmi J, Ghodsi R (2012) Supply chain network design problem for a new market opportunity in an agile manufacturing system. J Ind Eng Int 8:19

Ballou RH (2001) Unresolved issues in supply chain network design. Inform Syst Front 3(4):417–426. doi: 10.1023/A:1012872704057

Banks J, Carson JS, Nicol BL, Nelson DM (2001) Discrete event system simulation. Prentice Hall, Upper Saddle River

Beamon BM, Fernandes C (2004) Supply chain network configuration for product recovery. Prod Plan Control 15:270–281

Bulut G (2001) Robust multi-scenario optimization of an air expeditionary force structure applying scatter search to the combat forces assessment model. MS Thesis, Air Force Institute of Technology, Ohio, USA

Byrne MD, Bakir MA (1999) Production planning using a hybrid simulation–analytical approach. Int J Prod Econ 59(1):305–311

Byrne MD, Hossain MM (2005) Production planning: an improved hybrid approach. Int J Prod Econ 93–94:225–229

Chandra C, Grabis J (2007) Supply chain configuration: concept, solutions, and applications. Springer, New York

Cha-ume K, Chiadamrong N (2012) Simulation of retail supply chain behaviour and financial impact in an uncertain environment. Int J Logist Syst Manag 13(2):162–186

Claver JF, Coste B (1993) Paste plant design and control: a new approach. In: Light metals 1993 proceedings of the 122nd annual meeting, Denver, Colorado, pp 641–645

Cochran JK, Uribe AM (2005) A set covering formulation for agile capacity planning within supply chains. Int J Prod Econ 95:139–149

Fu MC (2002) Optimization for simulation: theory vs practice. Inform J Comput 14:192–215

Glover F, Kelly JP, Laguna M (1999) New advances for wedding optimization and simulation. In: The 1999 Winter Simulation Conference, pp 255–260

Hsieh SJ (2002) Hybrid analytic and simulation models for assembly line design and production planning. Simul Pract Theory 10:87–108

Izadi A, Kimiagari AM (2014) Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry. J Ind Eng Int 10:50. doi: 10.1007/s40092-014-0050-1

Keskin B, Melouk S, Meuer I (2010) A simulation-optimization approach for integrated sourcing and inventory decisions. Int J Comput Oper Res 37(9):1648–1661

Kleijnen JPC (2008) Design and analysis of simulation experiments. Springer, New York. doi: 10.1007/978-0-387-71813-2

Ko HJ, Ko CS, Kim T (2006) A hybrid optimization/simulation approach for a distribution network design of 3PLs. Comput Ind Eng 50(4):440–449

Kozan E (1997) Comparison of analytical and simulation planning models of seaport container terminal. Transport Plan Techn 20(3):235–248

Lee YH, Kim SH (2000) Optimal production-distribution planning in supply chain management using a hybrid simulation-analytic approach. In: The 2000 winter simulation conference, Orlando, FL, pp 1252–1259

Mehrdad M, Tu N, Miao L (2015) A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty. J Ind Eng Int 11:237–252. doi: 10.1007/s40092-014-0089-z

Melo MT, Nickel S, Saldanha-da-Gama F (2009) Facility location and supply chain management—a review. Eur J Oper Res 196(2):401–412

Mort N, Tsai CS (1996) Simulation and optimization in manufacturing systems using Taguchi methods. In: UKACC international conference on control' 96, University of Exeter, pp 467–471

Nikolopoulou A, Ierapetritou MG (2012) Hybrid simulation based optimization approach for supply chain management. Comput Chem Eng 47(20):183–193

Nolan RL, Sovereign MG (1972) A recursive optimization and simulation approach to analysis with an application to transportation systems. Manag Sci 18(12):676–690

Pereira MVF, Maceira MEP, Oliveria GC, Pinto LMVG (1992) Combining analytical models and Monte Carlo techniques in probabilistic power system analysis. IEEE T Power Syst 7(1):265–272

Pierce NG (1994) Golden nuggets of AMHS modeling and design for semiconductor wafer fabrication. In: The IEEE/SEMI 1994 advanced semiconductor manufacturing conference and workshop, Cambridge, MA, pp 200–204

Rabbani M, Ramezankhani F, Giahi R, Farshbaf-Geranmayeh A (2016) Biofuel supply chain considering depreciation cost of installed plants. J Ind Eng Int 12:221–235. doi: 10.1007/s40092-015-0139-1

Sargent RG (1994) Historical view of hybrid simulation/analytic models. In: The 1994 winter simulation conference. FL, pp 383–386

Swisher JR, Jacobson SH, Hyden PD, Schruben LW (2000) A survey of simulation and optimization techniques and procedures. In: The 2000 winter simulation conference, FL, pp 119–128

Tabrizi BH, Razmi J (2013) A multi-period distribution network design model under demand uncertainty. J Ind Eng Int. doi: 10.1186/2251-712X-9-13

Tavakkoli-Moghaddam R, Forouzanfar F, Ebrahimnejad S (2013) Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling. J Ind Eng Int 9:19

Thanh PN, Bostel N, Peton O (2008) A dynamic model for facility location in the design of complex supply chains. Int J Prod Econ 113(2):678–693