How to cite this paper
Dehbari, S., Pourrousta, A., Nezhad, S., Tavakkoli-Moghaddam, R & Javanshir, H. (2012). A new supply chain management method with one-way time window: A hybrid PSO-SA approach.International Journal of Industrial Engineering Computations , 3(2), 241-252.
Refrences
Chan, F.T.S., Chung, S.H., & Wadhwa, S. (2005). A hybrid genetic algorithm for production and distribution. Omega, 33(4), 345-355.
Chen, C., & Lee, W. (2004). Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices. Computers and Chemical Engineering, 28, 1131–1144.
Chan, Y., Carter, W.B., & Burnes, M.D. (2001). A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands. Computers & Operations Research, 28, 803-826.
Dasci, A., & Verter, V. (2001). A continuous model for production-distribution system design. European Journal of Operational Research, 129, 287-298.
Ibri, S. (2010). A parallel hybrid ant-tabu algorithm for integrated emergency vehicle dispatching and covering problem. International Journal of Innovative Computing and Application, 2(4), 226 – 236.
Jamili, A., Shafia, M.A., & Tavakkoli-Moghaddam, R. (2011). A hybrid algorithm based on particle swarm optimization and simulated annealing for a periodic job shop scheduling problem. International Journal of Advanced Manufacturing Technology, 54, 309-322.
Jayaraman, V., & Pirkul, H. (2001). Planning and coordination of production and distribution facilities for multiple commodities. European Journal of Operational Research, 133, 394-408.
Jayaraman, V., & Ross, A. (2003). A simulated annealing methodology to distribution network design and management. European Journal of Operational Research, 144, 629-645.
Kennedy, J., & Eberhart, R. )1995). Particle swarm optimization. In Proceeding of the 1995 IEEE international conference on neural network, Perth, Australia, 1942–1948.
Kirkpatrick, S., Gelatt, C. D., Jr., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220, 671–680.
Korpela, J., & Lehmusvaara, A. (1999). A customer oriented approach to warehouse network evaluation and design. International Journal of Production Economics, 59, 135–146.
Miranda, P.A., & Garrido, R.A. (2004). Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand. Transportation Research Part E, 40, 183–207.
Mokashi, S. D., & Kokossis, A.C. (2003). Application of dispersion algorithms to supply chain optimization. Computers and Chemical Engineering, 27, 927-949.
Nozick, L.K. (2001). The fixed charge facility location problem with coverage restrictions. Transportation research Part E, 37, 281-296.
Qu, W.W., Bookbinder, J.H., & Iyogun, P. (1999). An integrated inventory- transportation system with modified periodic policy for multiple products. European Journal of Operational Research, 115, 254-269.
Sabri, E.H., & Beamon, B.N. (2000). A multi-objective approach to simultaneous strategic and operational planning in supply chain design. Omega, 28, 581-598.
Shapiro, JF. (2001). Modeling the Supply Chain. Duxbury,Thomson learning.
Solomon, M.M. (1987). Algorithms for the vehicle routing and scheduling problem with time windows constraints. Operations Research, 35, 254–265.
Syarif, N., Yun, Y., Gen, M. (2002). Study on multi-stage logistic chain network: a spanning tree based genetic algorithm approach. Computers & Industrial Engineering, 43, 299-314.
Syam, S.S. (2002). A model and methodologies for the location problem with logistical components. Computers & Operations Research, 29, 1173-1193.
Wang, W., Fung, R.Y. K., & Chai, Y. (2003). Approach of just-in-time distribution requirements planning for supply chain management. International Journal of Production Economics, 91, 101-107.
Zhou, G., Min, H., & Gen, M. (2002). The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach. Computers & Industrial Engineering, 43, 251-261.
Chen, C., & Lee, W. (2004). Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices. Computers and Chemical Engineering, 28, 1131–1144.
Chan, Y., Carter, W.B., & Burnes, M.D. (2001). A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands. Computers & Operations Research, 28, 803-826.
Dasci, A., & Verter, V. (2001). A continuous model for production-distribution system design. European Journal of Operational Research, 129, 287-298.
Ibri, S. (2010). A parallel hybrid ant-tabu algorithm for integrated emergency vehicle dispatching and covering problem. International Journal of Innovative Computing and Application, 2(4), 226 – 236.
Jamili, A., Shafia, M.A., & Tavakkoli-Moghaddam, R. (2011). A hybrid algorithm based on particle swarm optimization and simulated annealing for a periodic job shop scheduling problem. International Journal of Advanced Manufacturing Technology, 54, 309-322.
Jayaraman, V., & Pirkul, H. (2001). Planning and coordination of production and distribution facilities for multiple commodities. European Journal of Operational Research, 133, 394-408.
Jayaraman, V., & Ross, A. (2003). A simulated annealing methodology to distribution network design and management. European Journal of Operational Research, 144, 629-645.
Kennedy, J., & Eberhart, R. )1995). Particle swarm optimization. In Proceeding of the 1995 IEEE international conference on neural network, Perth, Australia, 1942–1948.
Kirkpatrick, S., Gelatt, C. D., Jr., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220, 671–680.
Korpela, J., & Lehmusvaara, A. (1999). A customer oriented approach to warehouse network evaluation and design. International Journal of Production Economics, 59, 135–146.
Miranda, P.A., & Garrido, R.A. (2004). Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand. Transportation Research Part E, 40, 183–207.
Mokashi, S. D., & Kokossis, A.C. (2003). Application of dispersion algorithms to supply chain optimization. Computers and Chemical Engineering, 27, 927-949.
Nozick, L.K. (2001). The fixed charge facility location problem with coverage restrictions. Transportation research Part E, 37, 281-296.
Qu, W.W., Bookbinder, J.H., & Iyogun, P. (1999). An integrated inventory- transportation system with modified periodic policy for multiple products. European Journal of Operational Research, 115, 254-269.
Sabri, E.H., & Beamon, B.N. (2000). A multi-objective approach to simultaneous strategic and operational planning in supply chain design. Omega, 28, 581-598.
Shapiro, JF. (2001). Modeling the Supply Chain. Duxbury,Thomson learning.
Solomon, M.M. (1987). Algorithms for the vehicle routing and scheduling problem with time windows constraints. Operations Research, 35, 254–265.
Syarif, N., Yun, Y., Gen, M. (2002). Study on multi-stage logistic chain network: a spanning tree based genetic algorithm approach. Computers & Industrial Engineering, 43, 299-314.
Syam, S.S. (2002). A model and methodologies for the location problem with logistical components. Computers & Operations Research, 29, 1173-1193.
Wang, W., Fung, R.Y. K., & Chai, Y. (2003). Approach of just-in-time distribution requirements planning for supply chain management. International Journal of Production Economics, 91, 101-107.
Zhou, G., Min, H., & Gen, M. (2002). The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach. Computers & Industrial Engineering, 43, 251-261.