A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization

  • Li Wang
  • Junwei Zeng
  • Li Xu


In this paper, we studied a substage-zoning filling design problem, which is considered as a complex problem with numerous tasks such as construction planning, dam access road and borrow placement, workspace filling, and construction project management. In analyzing workflows and the mechanism of substage-zoning filling, not only the above-mentioned tasks are considered, but also the environmental factors such as rainfall and hydrology characteristic temperature are taken into account. In this study, an optimization model for dam filling which aimed at reducing the disequilibrium degree of filling intensity was proposed; in addition, a technique based on particle swarm optimization was introduced as the basis of a decision support system for rock-fill dams. The system has been employed in a water conservancy and hydropower project which shows that the system is able to provide quality decision support and facilitate the rock-fill dam construction effectively.


Substage-zoning filling design Rock-fill dam Decision support system Particle swarm optimization Leveling of production 



The authors acknowledge the support of the National Natural Science Foundation of China (Grant No 70971005), the Ministry of Science and Technology of China (Grant No 2006BAK04A23), Quality Inspection Project: Current State Analysis and Strategy Research about Consumer Products on Inspection and Testing Methods (Grant No 200910088) and Changjiang Scholars Program of the Ministry of Education of China.


  1. 1.
    Zhang Y, Xia G (2009) Construction of high embankment dam material flow equilibrium system. Expert Syst Appl 36(5):9175–9191CrossRefGoogle Scholar
  2. 2.
    Huang J, Wang D (2004) Research on staged-filling scheme about concrete-faced rock-fill dam of Hongjiadu hydropower station. Yangtze River 35(7):1–5Google Scholar
  3. 3.
    Ozkan M (1998) A review of considerations on seismic safety of embankments and earth and rock-fill dams. Soil Dyn Earthquake Eng 17(7–8):439–458CrossRefGoogle Scholar
  4. 4.
    Cetin H, Laman L, Ertunç A (2000) Settlement and slaking problems in the world’s fourth largest rock-fill dam, the Ataturk Dam in Turkey. Eng Geol 56(3–4):225–242CrossRefGoogle Scholar
  5. 5.
    Li S, Qin X (2005) The scheme for dam body fill and access roads to dam ccr arrangement of the Nuozhadu Hydropower Station. Water Power 31(5):66–71Google Scholar
  6. 6.
    Warfield JN (2007) Systems science serves enterprise integration: a tutorial. Enterp Inform Syst 1(2):235–254CrossRefGoogle Scholar
  7. 7.
    Xu L (2000) The contribution of systems science to information systems research. Syst Res Behav Sci 17:105–116CrossRefGoogle Scholar
  8. 8.
    Piao C, Han X, Wu H (2010) Research on e-commerce transaction networks using multi-agent modelling and open application programming interface. Enterp Inform Syst 4(3):329–353CrossRefGoogle Scholar
  9. 9.
    Kannan G, Matinez J, Vorster M (1997) A framework for incorporating dynamic strategies in earth-moving simulations. Proceedings of the 29th conference on Winter simulation. Atlanta, Georgia, pp 1119–1126Google Scholar
  10. 10.
    Zhang W, Lin Y (2010) On the principle of design of resilient systems-application to enterprise information systems. Enterp Inform Syst 4(2):99–110CrossRefGoogle Scholar
  11. 11.
    Zhang W (2010) Guest ediror’s foreword. Enterp Inform Syst 4(2):95–97CrossRefGoogle Scholar
  12. 12.
    Erol O, Sauser B, Mansouri M (2010) A framework for investigation into extended enterprise resilience. Enterp Inform Syst 4(2):111–136CrossRefGoogle Scholar
  13. 13.
    Liu D, Deters R, Zhang W (2010) Architectural design for resilience. Enterp Inform Syst 4(2):137–152CrossRefGoogle Scholar
  14. 14.
    Capozucca A, Guelfi N (2010) Modelling dependable collaborative time-constrained business processes. Enterp Inform Syst 4(2):153–214CrossRefGoogle Scholar
  15. 15.
    Wang J, Gao F, Ip W (2010) Measurement of resilience and its application to enterprise information systems. Enterp Inform Syst 4(2):215–223CrossRefGoogle Scholar
  16. 16.
    Xu L (1988) A fuzzy multi-objective programming algorithm in decision support systems. Ann Oper Res 12:315–320CrossRefGoogle Scholar
  17. 17.
    Xu L (1994) A decision support system for aids intervention and prevention. Int J Biomed Comput 36:281–291CrossRefGoogle Scholar
  18. 18.
    Feng S, Xu L (1997) An integrated knowledge-based system for urban planning decision support. Knowl-Based Syst 10:103–109CrossRefGoogle Scholar
  19. 19.
    Xu L, Li L (2000) A hybrid system applied to epidemic screening. Expert Syst 17:81–89CrossRefGoogle Scholar
  20. 20.
    Xu L, Liang N, Gao Q (2008) An integrated approach for agricultural ecosystem management. IEEE Trans Syst Man Cybern Part C 38(2):1–10Google Scholar
  21. 21.
    Xu L, Tan W, Zhen H, Shen W (2008) An approach to enterprise process dynamic modeling supporting enterprise process evolution. Inform Syst Front 10(5):611–624CrossRefGoogle Scholar
  22. 22.
    Feng S, Xu L (1999) Decision support for fuzzy comprehensive evaluation of urban development. Fuzzy Sets Syst 105(1):1–12CrossRefGoogle Scholar
  23. 23.
    Ogryczak W, Studzinski K, Zorychta K (1992) DINAS: a computer-assisted analysis system for multiobjective transshipment problems with facility location. Comput Oper Res 19(7):637–647CrossRefGoogle Scholar
  24. 24.
    Zhao H, Zhang Y, Wang Z, Lee S, Kwong W (2003) Research on group decision support system for concurrent product development process. J Mater Process Technol 139(1–3):619–623CrossRefGoogle Scholar
  25. 25.
    Xu L, Li Z, Li S, Tang F (2007) A decision support system for product design in concurrent engineering. Decis Support Syst 42(4):2029–2042CrossRefGoogle Scholar
  26. 26.
    Xu L, Li Z, Li S, Tang F (2005) A polychrommatic sets approach to the conceptual design of machine tools. Int J Prod Res 43(12):2397–2422CrossRefGoogle Scholar
  27. 27.
    Hastak M, Thakkallapalli S (2004) Decision model for assessment of underground pipeline rehabilitation options. Urban Water J 1(1):27–37CrossRefGoogle Scholar
  28. 28.
    Kumaraswamy M, Dissanayaka S (2001) Developing a decision support system for building project procurement. Build Environ 36(3):337–349CrossRefGoogle Scholar
  29. 29.
    Zavadskas E, Kaklauskas A, Vainiûnas P, Turski P (2003) Efficiency increase of internet based information systems in real estate sector by applying multiple criteria decision support systems. J Civ Eng Manag 9:83–90Google Scholar
  30. 30.
    Zeng J, Wang L, Wang T, Fan W, Gao H (2009) Particle swarm optimization-based machine arrangement for filling construction of rock-fill dams. IEEE International Conference on Industrial Engineering and Engineering Management, Hong Kong, pp 1772–1775Google Scholar
  31. 31.
    Al-Khaiat H, Fereig S (1996) The role of precast concrete systems in Kuwaiti housing projects–In-depth analysis of Kuwaiti precast concrete industry-Advantages and limitations of each system outlined. Build Res Inform 24(6):374–378CrossRefGoogle Scholar
  32. 32.
    Jackie R, Gary K (2002) Evolution in groups: a genetic algorithm approach to group decision support systems. Inf Technol Manage 3(3):213–227CrossRefGoogle Scholar
  33. 33.
    Luo J, Xu L, Jamont J, Zeng L, Shi Z (2007) Flood decision support system on agent grid: method and implementation. Enterp Inform Syst 1(1):49–68CrossRefGoogle Scholar
  34. 34.
    Feng S, Li L, Duan Z, Zhang J (2007) Assessing the impacts of south-to-north water transfer project with decision support systems. Decis Support Syst 42(4):1989–2003CrossRefGoogle Scholar
  35. 35.
    Zhou S, Xu L (1999) Dynamic recurrent neural networks for a hybrid intelligent decision support system for the metallurgical industry. Expert Syst 16(4):240–247CrossRefGoogle Scholar
  36. 36.
    Feng S, Xu L (1996) A hybrid knowledge-based system for urban development. Expert Syst Appl 10(1):157–163CrossRefGoogle Scholar
  37. 37.
    Feng S, Xu L (1996) Integrating knowledge-based simulation with aspiration-directed model-based decision support system. Syst Eng Electron 7(2):25–33Google Scholar
  38. 38.
    Xu L (1987) Toward escape from the limitations of systems analysis: introduction of dimensionality. Syst Res 4:243–250CrossRefGoogle Scholar
  39. 39.
    Feng W, Qu W, Xie H (2002) A note on the stresses of the ship lock of the Gezhouba project. J Mater Process Technol 123(2):241–244CrossRefGoogle Scholar
  40. 40.
    Wang L, Xu L, Wang X, You W, Tan W (2009) Knowledge portal construction and resources integration for a large scale hydropower dam. Syst Res Behav Sci 26(3):357–366CrossRefGoogle Scholar
  41. 41.
    Wang R, Liu J, Li S (2008) Optimization model for substage-zoning filling design of high core rock-fill dams. China Civ Eng J 41(2):105–110Google Scholar
  42. 42.
    Kutzner C (1989) Earth and rock-fill dams: principles of design and construction. Taylor & Francis, NetherlandsGoogle Scholar
  43. 43.
    Jansen R (1988) Advanced dam engineering for design, construction and rehabilitation. Springer, New YorkGoogle Scholar
  44. 44.
    Goodman R (1989) Introduction to rock mechanics. Wiley, New YorkGoogle Scholar
  45. 45.
    Kennedy J, Eberhart R (1995) Particle swarm optimization. Proceeding of IEEE international conference on neural networks. Piscataway, USA, pp 1942–1948 Google Scholar
  46. 46.
    Tao F, Zhang L, Lu K, Zhao D (2011) Research on manufacturing grid resource service optimal-selection and composition framework. Enterprise information systems first published on: 02 February 2011 (iFirst) doi: 10.1080/17517575.2010.540677
  47. 47.
    Yu W, Li R (2002) Study based on genetic glgorithms fot constrained optimization. Comput Sci 29(6):98–101Google Scholar
  48. 48.
    Wilke D, Kok S, Groenwold A (2006) Comparison of linear and classical velocity update rules in particle swarm optimization: notes on diversity. Int J Numer Methods Eng 70(8):962–984CrossRefGoogle Scholar
  49. 49.
    Vlachogiannis J, Lee K (2009) Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems. Expert Syst Appl 36(8):10802–10808CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Economics and ManagementBeihang UniversityBeijingChina
  2. 2.Jilin UniversityChangchunChina
  3. 3.University of Science and Technology of ChinaHefeiChina

Personalised recommendations