An inventory-theory-based interval-parameter two-stage stochastic programming model for water resources management

Engineering Optimization

Volumn 43, Issue 9, 2011, Pages 999-1018

  Suo, M Q ^a   Li, Y P ^a   Huang, G H ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

inventory; optimization; stochastic analysis; transfer water; uncertainty

Indexed keywords

CYCLE TIME; DECISION MAKERS; DECISION-MAKING PROBLEM; FLOW LEVEL; INVENTORY; INVENTORY THEORY; STOCHASTIC ANALYSIS; STOCHASTIC OPTIMIZATIONS; SYSTEM UNCERTAINTIES; TRANSFER WATER; TWO STAGE; TWO-STAGE STOCHASTIC PROGRAMMING; UNCERTAINTY; WATER ALLOCATIONS; WATER RESOURCES MANAGEMENT; WATER SHORTAGES;

COMPUTER PROGRAMMING; DECISION MAKING; OPTIMIZATION; PLANNING; STOCHASTIC MODELS; STOCHASTIC PROGRAMMING; STOCHASTIC SYSTEMS; WATER SUPPLY;

WATER RESOURCES;

EID: 84860403815     PISSN: 0305215X     EISSN: 10290273     Source Type: Journal    
DOI: 10.1080/0305215X.2010.528412     Document Type: Article

References (57)

1. Abbaspour, M. and Nobakhti, H., 2009. 3D model for evaluation of pollutant concentration distributions from land-based sources of the Caspian Sea Region-regional study, Southern Part of the Caspian Sea. Journal of Environmental Informatics, 14 (1), 51-65.
2. Ahmed, S., 2000. Strategic planning under uncertainty: Stochastic integer programming approaches. Thesis (PhD). University of Illinois, Urbana, IL.
3. Ahmed, S., Tawarmalani, M. and Sahinidis, N.V., 2004. A finite branch-and-bound algorithm for two-stage stochastic integer programs. Mathematical Programming, 100 (2), 355-377.
4. Birge, J.R. and Louveaux, F.V., 1988. A multicut algorithm for two-stage stochastic linear programs. European Journal of Operational Research, 34, 384-392.
5. Birge, J.R. and Louveaux, F.V., 1997. Introduction to stochastic programming. NewYork, NY: Springer.
6. Buckley, J.J., Feuring, T. and Hayashi,Y., 2000. Solving fuzzy problems in operations research: Inventory control. IEEE International Conference on Fuzzy Systems, 1, 352-357.
7. Cheng, T.C.E., 1989. An economic order quantity model with demand-dependent unit cost. European Journal of Operational Research, 40, 252-256.
8. Dada, M., Petruzzi, N. and Schwarz, L., 2007. A newsvendor's procurement problem when suppliers are unreliable. Manufacturing and Service Operations Management, 9 (1), 9-32.
9. Dai, L., Chen, C.H. and Birge, J.R., 2000. Convergence properties of two-stage stochastic programming. Journal of Optimization Theory and Applications, 106, 489-509.
10. Dantzig, G.B., 1983. Reminiscences about the origins of linear programming. Memoirs of the American Mathematical Society, 48 (298), 1-11.
11. EI Saadany, A.M.A. and Jaber, M.Y., 2010. A production/remanufacturing inventory model with price and quality dependent return rate. Computers & Industrial Engineering, 58 (3), 352-362.
12. Ferrero R.W., Rivera, J.F. and Shahidehpour, S.M., 1998. A dynamic programming two-stage algorithm for long-term hydrothermal scheduling of multireservoir systems. IEEE Transactions on Power Systems, 13, 1534-1540.
13. Gelders, L.F. and van Looy, P.M., 1978. An inventory policy for slow and fast movers in a petrochemical plant: A case study. Journal of the Operational Research Society, 29 (9), 867-874.
14. Guo, P. and Huang, G.H., 2009. Two-stage fuzzy chance-constrained programming - application to water resources management under dual uncertainties. Stochastic Environmental Research and Risk Assessment, 23, 349-359.
15. Hadley, G. and Whitin, T.M., 1963. Analysis of inventory systems. Englewood Cliffs, NJ: Prentice-Hall.
16. Harrison, K.W., 2007. Two-stage decision-making under uncertainty and stochasticity: Bayesian programming. Advances in Water Resources, 30, 641-664.
17. Haurie, A. and Moresino, F., 2000. A stochastic programming approach to manufacturing flow control. IIE Transactions, 32, 907-920.
18. Hillier, F.S. and Lieberman, G.J., 2001. Introduction to operations research. 7th edn. NewYork: McGraw-Hill.
19. Huang, G.H., Baetz,B.W. and Patry, G.G., 1995. Grey integer programming:Anapplication towaste management planning under uncertainty. European Journal of Operational Research, 83, 594-620.
20. Huang, G.H., 1998. A hybrid inexact-stochastic water management model. European Journal of Operational Research, 107, 137-158.
21. Huang, G.H. and Loucks, D.P., 2000.Aninexact two-stage stochastic programming model forwater resources management under uncertainty. Civil Engineering and Environmental Systems, 17, 95-118.
22. Huang, K. and Ahmed, S., 2010. A stochastic programming approach for planning horizons of infinite horizon capacity planning problems. European Journal of Operational Research, 200, 74-84.
23. Huang, W.C., Liaw, S.L. and Chang, S.Y., 2010. Development of a systematic object-event data model of the database system for industrial wastewater treatment plant management. Journal of Environmental Informatics, 15 (1), 14-25.
24. Jakeman, A.J., Letcher, R.A. and Norton, J.P., 2006. Ten iterative steps in development and evaluation of environmental models. Environmental Modelling & Software, 21 (5), 602-614.
25. Kao, C. and Hsu, W., 2002. A single-period inventory model with fuzzy demand. Computer & Mathematics with Applications, 43 (6-7), 841-848.
26. Kar, S., Roy, T.K. and Maiti, M., 1999. Fuzzy multi-deteriorating items EOQ model with price dependent under budgetary constraint. Modelling, Measurement and Control D, 19, 245-259.
27. Kelman, J., Stedinger, J.R., Cooper, L.A., Hsu, E. and Yuan, S.-Q., 1990. Sampling stochastic dynamic programming applied to reservoir operation. Water Resources Research, 26 (3), 447-454.
28. Kovacs, L., Boros, E. and Inotay, F., 1986.A two-stage approach for large-scale sewer systems design with application to the Lake Balaton resort area. European Journal of Operational Research, 23 (2), 169-178.
29. Kukreja, A. and Schmidt, C.P., 2005. A model for lumpy demand parts in a multi-location inventory system with transshipments. Computers and Operations Research, 32 (8), 2059-2075.
30. Kunnumkal, S. and Topaloglu, H., 2006. Using stochastic approximation methods to compute optimal base-stock levels in inventory control problems. Operations Research, 56 (3), 646-664.
31. Li, Y.P., Huang, G.H. and Nie, S.L., 2006. An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty. Advances in Water Resources, 29 (5), 776-789.
32. Li, Y.P., Huang, G.H. and Nie, S.L., 2007. Mixed interval-fuzzy two-stage integer programming and its application to flood-diversion planning. Engineering Optimization, 39 (2), 163-183.
33. Li,Y.P., Huang, G.H., Nie, S.L. and Mo, D.W., 2008a. Interval-parameter robust quadratic programming for water quality management under uncertainty. Engineering Optimization, 40 (7), 613-635.
34. Li,Y.P., Huang, G.H., Nie, S.L. and Liu, L., 2008b. Inexact multistage stochastic integer programming for water resources management under uncertainty. Journal of Environmental Management, 88 (1), 93-107.
35. Li,Y.P., Huang, G.H., Huang,Y.F. and Zhou, H.D., 2009.Amultistage fuzzy-stochastic programming model for supporting sustainable water-resources allocation and management. Environmental Modelling & Software, 24, 786-797.
36. Liu, N.Y., Paranjape, R. and Asghari, K., 2010. Modeling acoustic properties of the fluid-fluid interface in porous medium. Journal of Environmental Informatics, 15 (1), 26-32.
37. Loucks, D.P., Stedinger, J.R. and Haith, D.A., 1981. Water resource systems planning and analysis. Englewood Cliffs, NJ: Prentice-Hall.
38. Maiti, A.K., Maiti, M.K. and Maiti, M., 2009. Inventory model with stochastic lead-time and price dependent demand incorporating advance payment. Applied Mathematical Modelling, 33, 2433-2443.
39. Mandal, N.K. and Roy, T.K., 2006.Adisplayed inventory model with L-R fuzzy number. Fuzzy Optimization and Decision Making, 5 (3), 227-243.
40. Maqsood, I. and Huang, G.H., 2003. A two-stage interval-stochastic programming model for waste management under uncertainty. Journal of the Air & Waste Management Association, 53 (5), 540-552.
41. Maqsood, I., Huang, G.H. andYeomans, J.S., 2005. An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty. European Journal of Operational Research, 167, 208-225.
42. Porras, E. and Dekker, R., 2008. An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods. European Journal of Operational Research, 184 (1), 101-132.
43. Roy, T.K. and Maiti, M., 1997. A fuzzy EOQ model with demand-dependent unit cost under limited storage capacity. European Journal of Operational Research, 99, 425-432.
44. Ruszczynski, A., 1993. Parallel decomposition of mulitsatge stochastic programming problems. Mathematical Programming, 58, 201-228.
45. Ruszczynski, A. and Swietanowski, A., 1997. Accelerating the regularized decomposition method for two-stage stochastic linear problems. European Journal of Operational Research, 101, 328-342.
46. Schmitt, A.J., Snyder, L.V. and Max Shen, Z.-J., 2010. Inventory systems with stochastic demand and supply: Properties and approximations. European Journal of Operational Research, 206, 313-328.
47. Schultz, R., Stougie, L. and van der Vlerk M.H., 1995. Two-stage stochastic integer programming: A survey. Statistica Neerlandica, 50 (3), 404-416.
48. Seifi, A. and Hipel, K.W., 2001. Interior-point method for reservoir operation with stochastic inflows. Journal of Water Resources Planning and Management, 127 (1), 48-57.
49. Taha, H.A., 1976. Operations research - An introduction. 2nd edn. NewYork: Macmillan.
50. Trezos, T. andYeh,W.W.-G., 1987. Use of stochastic dynamic programming for reservoir management.Water Resources Research, 23, 983-996.
51. Udayalaxmi, G., Ramadass, G. and Himabindu, D., 2009. Geochemical evaluation of groundwater quality in Katedhan IDA and surrounding areas, Hyderabad, A.P., India. Journal of Environmental Informatics, 14 (2), 100-109.
52. Urgeletti Tinarelli, G., 1983. Inventory control models and problems. European Journal of Operational Research, 14, 1-12.
53. Vereecke, A. andVerstraeten, P., 1994. An inventory management model for an inventory consisting of lumpy items, slow movers and fast movers. International Journal of Production Economics, 35 (1-3), 379-389.
54. Willemain, T.R., Smart, C.N. and Schwarz, H.F., 2004. A new approach to forecasting intermittent demand in manufacturing:Acomparative evaluation of Croston's method. International Journal of Forecasting, 10 (4), 529-538.
55. Xu, R.N. and Zhai, X.Y., 2010. Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain. Applied Mathematical Modelling, 34, 129-139.
56. Xu, Y., Huang, G.H. and Qin, X.S., 2009. Inexact two-stage stochastic robust optimization model for water resources management under uncertainty. Environmental Engineering Science, 26 (12), 1765-1776.
57. Zhang, X.H., Zhang, H.W., Chen, B., Guo, H.C., Chen, G.Q. and Zhao, B.A., 2009. An inexact-stochastic dual water supply programming model. Communications in Nonlinear Science and Numerical Simulation, 14, 301-309.