Journal of Innovative Research in Engineering Sciences



Application of Genetic Algorithms to Optimize Heavy Earthworks Operations

Farshad Asadbeigi, Ali Golsoorat Pahlaviani, Javad Majrouhi Sardroud

Most of the major projects in the construction industry are faced with earthwork operations, so that one can rarely find a construction project that does not have such operations. For infrastructure projects, ground operations are one of the major areas of the project, and a wide range of construction machinery is used to carry out earthwork operations. Soil operations are one of the most important and costly parts of construction projects and projects for harvesting materials from surface mines. One of the important factors in the success of large projects and projects such as dam, road, tunnel and more is the role of machinery and, consequently, the way of selecting and managing it properly. Due to the large scale of construction projects, even a small improvement in operation operations can save a lot of work. One of the major costs of infrastructure is the cost of ground operations. Therefore, the purpose of this study is to use the genetic algorithm to optimize heavy soil operations for proposing a method for developing a method to optimize large-scale earth-borne operations for the lowest cost of land operations.

Published on the web: 2018-09-24
Received : 2018-07-10
Submitting : 2018-06-12
Keyword:1- genetic algorithm
Keyword:2- Earthworks
Keyword:3- optimization,
Keyword:4- road construction machinery

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  1. Gen M, Cheng R. Genetic algorithms and engineering optimization. John Wiley & Sons; 2000.[Scholar]
  2. Rashidi, Ozbayi, Optimum allocation of road construction machinery in land use projects, International Road and Building Monthly, 2004. [Scholar]
  3. Rogalska M, Bo?ejko W, Hejducki Z. Time/cost optimization using hybrid evolutionary algorithm in construction project scheduling. Automation in Construction. 2008 Dec 1;18(1):24-31. [Scholar]
  4. Southworth F. A Technical Review of Urban Land Use--Transportation Models as Tools for Evaluating Vehicle Travel Reduction Strategies.[Scholar]
  5. Parente M, Correia AG, Cortez P. A novel integrated optimization system for earthwork tasks. 6th Transport Research Arena (TRA 2016). 2016;14:3601-10.[Scholar]
  6.  Aziz RF, Aboel-Magd YR. Suitably selection for earthwork equipment in Egyptian sites. International Journal of Education and Research. 2015 Jan;3(1):539-50. [Scholar]
  7. Parente M, Correia AG, Cortez P. Metaheuristics, Data Mining and Geographic Information Systems for Earthworks Equipment Allocation. Procedia engineering. 2016 Jan 1;143:506-13.[Scholar]
  8. Hsiao WT, Lin CT, Wu HT, Cheng TM. A hybrid optimization mechanism used to generate truck fleet to perform earthmoving operations. InRoad Materials and New Innovations in Pavement Engineering 2011 (pp. 151-159).[Scholar]
  9. Parente M, Cortez P, Correia AG. An evolutionary multi-objective optimization system for earthworks. Expert Systems with Applications. 2015 Nov 1;42(19):6674-85.[Scholar]
  10. SUN Q, SANG CL, LIN BL. Virtual design of the mechanical system of the quadruped robot and theory analysis of the wheel mechanism [J]. Machinery Design & Manufacture. 2009;8:076. [Scholar]
  11. Kandil A, El-Rayes K. Parallel genetic algorithms for optimizing resource utilization in large-scale construction projects. Journal of Construction engineering and Management. 2006 May;132(5):491-8.[Scholar]
  12. Dzeng RJ, Lee HY. Optimizing the development schedule of resort projects by integrating simulation and genetic algorithm. International Journal of Project Management. 2007 Jul 1;25(5):506-16.[Scholar]
  13. Burt CN, Caccetta L. Equipment selection for surface mining: a review. Interfaces. 2014 Apr;44(2):143-62. [Scholar]
  14. Jang H, Topal E. A review of soft computing technology applications in several mining problems. Applied Soft Computing. 2014 Sep 1;22:638-51.[Scholar]
  15. Moselhi O, Alshibani A. Optimization of earthmoving operations in heavy civil engineering projects. Journal of Construction Engineering and Management. 2009 Sep 15;135(10):948-54.[Scholar]
  16. Razavialavi S. Construction Site Layout Planning Using Simulation (Doctoral dissertation, University of Alberta). [Scholar]
  17. Naskoudakis I, Petroutsatou K. A thematic review of main researches on construction equipment over the recent years. Procedia engineering. 2016 Jan 1;164:206-13.[Scholar]
  18.  Hare WL, Koch VR, Lucet Y. Models and algorithms to improve earthwork operations in road design using mixed integer linear programming. European Journal of Operational Research. 2011 Dec 1;215(2):470-80.[Scholar]
  19. Parente M, Correia AG, Cortez P. Metaheuristics, Data Mining and Geographic Information Systems for Earthworks Equipment Allocation. Procedia engineering. 2016 Jan 1;143:506-13. [Scholar]
  20. Ugwu OO, Tah JH. Towards optimising construction-method selection strategies using genetic algorithms. Engineering Applications of Artificial Intelligence. 1998 Aug 1;11(4):567-77.[Scholar]
  21. Naseri F. Dynamic Mechanical Behavior of Rock Materials. Journal of Civil Engineering and Materials Application. 2017 Oct 17;1(2):39-44.[Scholar]