Stochastic dynamic lot-sizing problem using bi-level programming base on artificial intelligence techniques

Applied Mathematical Modelling

Volumn 36, Issue 5, 2012, Pages 2003-2016

  Wong, Jui Tsung ^a   Su, Chwen Tzeng ^b   Wang, Chun Hsien ^c  

^a SHIH CHIEN UNIVERSITY   (Taiwan)

^b NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^c NATIONAL CHIAYI UNIVERSITY   (Taiwan)

Author keywords

Ant colony optimization; Artificial neural network; Deteriorating commodity; Lot sizing problem; Simulation

Indexed keywords

ANT-COLONY OPTIMIZATION; ARTIFICIAL NEURAL NETWORK; DETERIORATING COMMODITY; LOT SIZING PROBLEMS; SIMULATION;

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; DETERIORATION; INTELLIGENT SYSTEMS; OPTIMIZATION; REAL VARIABLES; STOCHASTIC SYSTEMS;

NEURAL NETWORKS;

EID: 84855834187     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2011.08.017     Document Type: Article

References (31)

1. Vidal C.J., Goetschalckx M. Strategic production-distribution models. Eur. J. Oper. Res. 1997, 98:1-18.
2. Ben-Ayed O., Boyce D.E., Blair C.E. A general bilevel linear programming formulation of the network design problem. Transport Res. B 1988, 22:311-318.
3. Kalashnikov V.V., Ríos-Mercado R.Z. A natural gas cash-out problem: a bilevel programming framework and a penalty function method. Optimiz. Eng. 2006, 7:403-420.
4. Campêlo M., Scheimberg S. A simplex approach for finding local solutions of a linear bilevel program by equilibrium points. Ann. Oper. Res. 2005, 138:143-157.
5. Mishra S., Ghosh A. Interactive fuzzy programming approach to bi-level quadratic fractional programming problems. Ann. Oper. Res. 2006, 143:251-263.
6. Colson B., Marcotte P., Savard G. A trust-region method for nonlinear bilevel programming: algorithm and computational experience. Comput. Optimiz. Appl. 2005, 30:211-227.
7. Jaruphongsa W., Cetinkaya S., Lee C.Y. Warehouse space capacity and delivery time window considerations in dynamic lot-sizing for a simple supply chain. Int. J. Prod. Econ. 2004, 92:169-180.
8. Hsieh T.P., Dye C.Y., Ouyang L.Y. Optimal lot size for an item with partial backlogging rate when demand is stimulated by inventory above a certain stock level. Math. Comput. Modell. 2010, 51:13-32.
9. Gao L.L., Altay N., Robinson E.P. A comparative study of modeling and solution approaches for the coordinated lot-size problem with dynamic demand. Math. Comput. Modell. 2008, 47:1254-1263.
10. Lee C.Y., Cetinkaya S., Jaruphongsa W. A dynamic model for inventory lot sizing and outbound shipment scheduling at a third-party warehouse. Oper. Res. 2003, 51:735-747.
11. Özdamar L., Birbil S.I. Hybrid heuristics for the capacitated lot sizing and loading problem with setup times and overtime decisions. Eur. J. Oper. Res. 1998, 110:525-547.
12. Wong J.T., Chen K.H., Su C.T. Replenishment policy with deteriorating raw material under a supply chain: complexity and the use of ant colony optimization. Lect. Notes Business Inform. Process. 2009, 20:142-152.
13. Soman C.A., Pieter van Donk D., Gaalman G. Comparison of dynamic scheduling policies for hybrid make-to-order and make-to-stock production systems with stochastic demand. Int. J. Prod. Econ. 2006, 104:441-453.
14. Chandra C., Grabis J. Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand. Eur. J. Oper. Res. 2005, 166:337-350.
15. Alstrøm P., Madsen P. Tracking signals in inventory control systems: a simulation study. Int. J. Prod. Econ. 1996, 45:293-302.
16. Jammemegg W., Reiner G. Performance improvement of supply chain processes by coordinated inventory and capacity management. Int. J. Prod. Econ. 2007, 108:183-190.
17. Machuca J.A.D., Barajas R.P. The impact of electronic data inter change on reducing bullwhip effect and supply chain inventory costs. Transport. Res. Part E: Logist. Transport. Rev. 2004, 40:209-228.
18. Fleisch E., Tellkamp C. Inventory inaccuracy and supply chain performance: a simulation study of a retail supply chain. Int. J. Prod. Econ. 2005, 95:373-385.
19. Ravichandran N. A finite horizon inventory model: an operational framework. Int. J. Prod. Econ. 2007, 108:406-415.
20. Gumus A.T., Guneri A.F., Ulengin F. A new methodology for multi-echelon inventory management in stochastic and neuro-fuzzy environments. Int. J. Prod. Econ. 2010, 128:248-260.
21. Rohde J. Hierarchical supply chain planning using artificial neural networks to anticipate base-level outcomes. OR Spectrum 2004, 26:471-492.
22. Lee Y.H., Jung J.W., Eum S.C., Park S.M., Nam H.K. Production quantity allocation for order fulfillment in the supply chain: a neural network based approach. Prod. Plan. Control 2006, 17:378-389.
23. Gumus A.T., Guneri A.F. A multi-echelon inventory management framework for stochastic and fuzzy supply chains. Expert Syst. Appl. 2009, 36:5565-5575.
24. Lee C.C., Ou-Yang C. A neural networks approach for forecasting the supplier's bid prices in supplier selection negotiation process. Expert Syst. Appl. 2009, 36:2961-2970.
25. Sadeghi Moghadam M.R., Afsar A., Sohrabi B. Inventory lot-sizing with supplier selection using hybrid intelligent algorithm. Appl. Soft Comput. 2008, 8:1523-1529.
26. Wong J.T., Su C.T., Hsieh H.T. A framework for determining MIMO process parameters by neuro-DM&ACO approach. Int. J. Prod. Res. 2007, 45:3505-3520.
27. Wong J.T., Su C.T., Chen K.H. Replenishment policy based on modified ant colony optimization and statistical analysis under the pre-order penetration point. Int. J. Comput. Math. 2009, 86:477-491.
28. Myers R.H., Montgomery D.C. Response surface methodology: process and product optimization using designed experiments 2002, John Wiley and Sons, New York, NY. second ed.
29. Gharbi A., Kenné J.-P. Maintenance scheduling and production control of multiple-machine manufacturing systems. Comput. Ind. Eng. 2005, 48:693-707.
30. Horng H.-C., Cochran J.K. Project surface regions: a decision support methodology for multitasking workers assignment in JIT systems. Comput. Ind. Eng. 2001, 39:159-171.
31. Aksoy A., Öztürk N. Supplier selection and performance evaluation in just-in-time production environments. Expert Syst. Appl. 2011, 38:6351-6359.