Tunneling method selection is a critical point and a strategic issue in the planning stage of a tunneling project. Compatibility of a selected tunneling method with the geological and geotechnical conditions is crucial to success of a tunneling project. On the other hand, use of a decision-making process is inevitable with regard to many geological and geotechnical variables and uncertainties and also unpredictable ground conditions during tunneling operation. So, use of an efficient decision making technique which can take into account several criteria in such conditions is necessary. This paper develops an evaluation model based on the analytic hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS), to help the engineers in tunneling industries for the selection of optimal tunneling methods in a fuzzy environment. The fuzzy-AHP is used to determine global weights of the criteria and fuzzy TOPSIS method is used to obtain final ranking of alternatives. This approach is applied to select optimal tunneling method among six tunneling techniques including open TBM, double shield TBM, single shield TBM, roadheader, drilling & blasting and hydraulic hammer in Zagros water transfer tunnel of Iran. Finally, double shield TBM was selected as optimal tunneling method in Zagros water transfer tunnel of Iran.
Selection of the proper tunneling methods for use in various ground conditions is a very delicate and important part of planning a tunneling project. This is because this decision is almost irreversible and if the selective tunneling method be not suitable for the ground conditions, it can cause major delays, could be detrimental to the safety of the crew and personnel, and ultimately could bring the project to a halt. Obviously, accurate characterization of the ground using surface and subsurface investigation will allow the designers to foresee the potential problems and select a method that can cope with the anticipated conditions. This often means selecting a method that can offer optimum performance in the given conditions, and sometimes adding special features and devices that could provide the flexibility and capability to mitigate adverse ground conditions. In brief, selection of a proper tunneling method with the right technical specifications and functionalities is important to ensure the speedy, safe, and successful completion of the tunnel project within the requirements of the contract. However, by its very nature, subsurface investigation and ground characterization can be all but certain. There are multiple levels of uncertainty involved in ground characterization starting from the location of the borings, formations or layers that could be missed in the drilling program, proper logging and characterization of the lithotypes, accurate measurement of the rock properties in the field and laboratory testing, issues of groundwater and their sources, in situ stresses, and so on [1]. This indicates the need for additional tools for assisting the decision making in the design and construction stage. Typical tools at the engineer's disposal are statistical methods, systematic risk assessment methods and, more recently, artificial intelligence (AI) approaches such as neural networks and fuzzy logic.
