Modeling (r, Q) policy in a two-level supply chain system with fuzzy demand

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 18, Issue 6, 2010, Pages 819-841

  Pirayesh, Mohammadali ^a   Yazdi, Mohammad Modarres ^b  

^a FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

^b SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

fuzzy set; genetic algorithm; inventory control; Supply chain

Indexed keywords

CHAINS; FUZZY SETS; GENETIC ALGORITHMS; MEMBERSHIP FUNCTIONS; NONLINEAR PROGRAMMING; NUMERICAL METHODS; SUPPLY CHAINS;

FUZZY DEMAND; HOLDING COSTS; INVENTORY CONTROL POLICIES; NEAR-OPTIMAL SOLUTIONS; ORDERING COST; SHORTAGE COST; SUPPLY CHAIN SYSTEMS; TRIANGULAR MEMBERSHIP FUNCTIONS; UNSATISFIED DEMAND;

INVENTORY CONTROL;

EID: 78649585823     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488510006817     Document Type: Article

References (29)

1. S. Chopra and P. Meindl, Supply Chain Management: Strategy, Planning, and Operation (Prentice Hall, New Jersey, 2001).
2. J. Wang and Y. F. Shu, Fuzzy decision modeling for supply chain management, Fuzzy Sets and Systems 150(2005) 107-127.
3. R. Ganeshan, Managing supply chain inventories: A multiple retailer, one warehouse, multiple supplier model, Int. J. Production Economics 59(1999) 341-354.
4. J. Andersson and J. Marklund, Decentralized inventory control in a two-level distribution system, European J. Operational Research 127(2000) 483-506.
5. M. Seifbarghy and M. R. Akbari, Cost evaluation of a two-echelon inventory system with lost sales and approximately Poisson demand, Int. J. Production Economics 102(2006) 244-254.
6. D. Petrovic, Simulation of supply chain behaviour and performance in an uncertain environment, Int. J. Production Economics 71(2001) 429-438.
7. D. Petrovic, R. Roy and R. Petrovic, Modelling and simulation of a supply chain in an uncertain environment, European J. Operational Research 109(1998) 299-309.
8. D. Petrovic, R. Roy and R. Petrovic, Supply chain modelling using fuzzy sets, Int. J. Production Economics 59(1999) 443-453.
9. I. Giannoccaro, P. Pontrandolfo and B. Scozzi, A fuzzy echelon approach for inventory management in supply chains, European J. Operational Research 149(2003) 185-196.
10. Y. Xie, D. Petrovic and K. Burnham, A heuristic procedure for the two-level control of serial supply chains under fuzzy customer demand, Int. J. Production Economics 102(2006) 37-50.
11. M. Gen, Y. Tsujimura and D. Zheng, An application of fuzzy set theory to inventory control model, Computers and Industrial Engineering 33(1997) 553-556.
12. S. Chang, J. Yao and H. Lee, Economic reorder point for fuzzy backorder quantity. European J. Operational Research 109(1998) 183-202.
13. L. Ouyang and J. Yao, A minimax distribution free procedure for mixed inventory model involving variable lead time with fuzzy demand, Computers and Operations Research 29(2002) 471-487. (Pubitemid 33098646)
14. M. Modarres Yazdi and M. Pirayesh, (r, Q) & (R, T) policies with backorder for fuzzy demand, Department of IE, Sharif University of Technology, Working Paper 2002.
15. R. M. Hill, The single-vendor single-buyer integrated production-inventory model with a generalized policy, European J. Operational Research 97(1997) 493-499.
16. M. A. Hoque and S. K. Goyal, An optimal policy for a single-vendor single-buyer integrated production-inventory system with capacity constraint of the transport equipment, Int. J. Production Economics 65(2000) 305-315.
17. S. K. Goyal and F. Nebebe, Determination of economic production-shipment policy for a single-vendor-single-buyer system, European J. Operational Research 121(2000) 175-178.
18. Y. Abdel-Magid and M. Abido, Optimal multiobjective design of robust power system stabilizers using genetic algorithms, IEEE Trans. PWRS 18(2003) 1125-1132.
19. J. H. Holland, Adaptation in Natural and Artificial Systems, 2nd edn., (University of Michigan Press, MIT Press, 1992).
20. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning (Addison-Wesley, MA., 1989).
21. M. Gen and R. Cheng, Genetic Algorithms and Engineering Design (Wiley, New York, 1997).
22. Y. Liang, K. S. Leung and Z. B. Xu, A novel splicing/decomposable binary encoding and its operators for genetic and evolutionary algorithms, Applied Mathematics and Computation 190(2007) 887-904.
23. K. Lee, X. Bai and Y. Park, Optimization method for reactive power planning by using a modified simple genetic algorithm, IEEE Trans. PWRS 10(1995) 1843-1850.
24. X. Yang, Z. Yang and J. Li, A gray-encoded, hybrid-accelerated, genetic algorithm for global optimizations in dynamical systems, Communications in Nonlinear Science and Numerical Simulation 10(2005) 355-363. (Pubitemid 39408092)
25. J. J. Grefenstette, Optimization of control parameters for genetic algorithms, IEEE Trans. Systems, Man, and Cybernetics SMC-16 (1986) 122-128.
26. S. F. Hwang and R. S. He, Improving real-parameter genetic algorithm with simulated annealing for engineering problems, Advances in Engineering Software 37(2006) 406-418.
27. K. A. De Jong, "An Analysis of the behavior of a class of genetic adaptive systems", Ph. D. thesis (University of Michigan, 1975).
28. M. Khouja, Z. Michalewicz and M. Wilmot, The use of genetic algorithms to solve the economic lot size scheduling problem, European J. Operational Research 110(1998) 509-524.
29. N. Hayat and A. Wirth, Genetic Algorithms and Machine Scheduling With Class Setups, Int. J. Computer and Engineering Management 5(1997) 10-23.