With China’s hydropower development and improvement of construction technology, underground powerhouse is increasingly growing both in number and scale, which brings about challenge for construction management. Schedule is the focus of construction management of underground powerhouse. However, the construction is not only faced with challenges such as tight construction schedule, complex construction technology, plenty of uncertain factors, etc., but also faces problem about how to enable schedule plan more effectively guide practical construction. It is the research emphasis for current schedule study on underground powerhouse to find solution to above problems. This paper makes an in-depth study on the problems mentioned above and obtains the following results:1. Probability distribution of various uncertain parameters in construction schedule analysis of underground powerhouse is determined. In addition, Markov chain Monte Carlo(MCMC) sampling method and sensitivity analysis method based on uniform design are adopted to make sampling and optimization of diverse simulation parameters.There exist various kinds of uncertain factors during the underground powerhouse construction. Although current schedule simulation research has taken uncertain factors into consideration, it only makes probability analysis of stochastic activity duration to calculate completion probability, and does not consider other uncertainty such as lithology, construction disturbance and so on. Moreover, current construction schedule simulation mainly adopts Monte Carlo(MC) method to simulate uncertain factors. This method is not satisfactory when considering its deficiencies, including large number of simulation times, instability of simulation results, taking no consideration of correlation between random sequences and so on. Considering the problem mentioned above, this paper first analyzes the probability distribution of uncertain simulation input parameters. Next, Markov probability transition equation is adopted to improve analysis method of lithological probability distribution. Finally, this paper adopts MCMC method to make sampling of uncertain simulation input parameters, and considers the interaction of parameter’s sampling status with Markov probability transition equation, which overcomes the drawbacks of MC method and provides input data for construction schedule simulation, robustness analysis and optimization. In addition, sensitivity analysis method based on uniform design is used to analyze the impact that change of resource allocation parameter makes on construction period, which provides scientific basis for optimizing initial plan in construction organization design and determination of key parameters in practical construction schedule control.2. With comprehensive consideration of uncertain factors during underground powerhouse construction, this paper proposes construction schedule simulation theory and modeling method of underground powerhouse based on uncertainty analysis.Current construction schedule simulation of underground powerhouse does not pay enough attention to uncertain factors such as lithology, mechanical breakdown, construction disturbance and so on. Considering above problem, this paper establishes construction schedule simulation model, which is built based on uniform design and couples Critical Path Method(CPM) and Cycle Operation Network(CYCLONE). First, MCMC method is used to sample input parameters of simulation model that is set up based on uncertainty analysis, and the uncertainty of activity duration is taken into account with the probability distribution function. Then, Markov probability transition equation is adopted to improve selection method of lithology parameter in simulation model, and the more accurate analysis of uncertainty of lithology parameter can thus be realized. Finally, in order to simulate schedule with the occurrence of construction disturbance, this paper adds system dynamics module into simulation model and realizes construction schedule simulation with the consideration of change of equipment failure rate, which provides convenient approach for construction schedule robustness analysis.3. Considering the impact that project crashing degree makes on equipment failure rate, this paper establishes construction schedule simulation model, which considers the effect of equipment failure rate and couples system dynamics and discrete event simulation.Current underground powerhouse simulation adopts discrete event simulation method to simulate construction process. This approach does not consider the interaction of construction schedule and mechanical failure. What’s more, the method that uses random function to conduct MCMC sampling of equipment failure does not take the change of equipment failure rate into account. Therefore, this paper sets up system dynamics model that considers the mutual effect of mechanical failure and construction schedule. This model uses the feedback relation of diverse project crashing degree to simulate the variation of equipment failure rate; adopts stochastic probability distribution to describe time delay and other variables; includes auxiliary variables such as “sudden wearâ€, and considers the uncertainty of mechanical failure from different aspects. Furthermore, with the consideration of equipment failure rate, this paper establishes simulation model coupling construction schedule system dynamics and discrete event simulation. This model takes full advantages that discrete event simulation focuses on the analysis of technical details, and system dynamics puts emphasis on analyzing causal relationship between variables or continuous change process from the overall perspective of construction system, then provides reliable basis to predict construction period and robustness index under construction disturbance.4. In order to improve the capacity of resisting disturbance of construction schedule, research on the construction schedule robustness and its analysis index of underground powerhouse is conducted in this paper.Current research regards shortest construction period as simulation target, and does not consider the capacity that construction schedule resists uncertain disturbance. Considering the above deficiencies, according to the logical structure of construction schedule simulation model, this paper puts forward two indexes-duration deviation and structure deviation, to evaluate construction schedule robustness, and provides more comprehensive basis for evaluating construction schedule robustness. What’s more, method for determining robustness construction schedule buffer based on critical chain is proposed, which can not only consider logic relationship between activities, but take the impact that resource constraint makes on buffer into account. In addition, this paper builds construction schedule optimization model which targets the integrated optimization of construction period and robustness, then uses genetic algorithm to solve the model, and finally provides basis for make construction scheme with high robustness.5. Considering the restriction relation of construction period and robustness, this paper proposes scheme evaluation and optimization method of underground powerhouse construction schedule simulation based on Data Envelopment Analysis(DEA).As two key factors of underground powerhouse construction, construction period and robustness have close relationship. They are mutual restraint, and when one aspect wanes, the other waxes. Current research on scheme optimization of underground powerhouse construction simulation mostly adopts linear weighting method based on Delphi method or multi-objective programming with analytic hierarchy process. These approaches have the shortcomings of high reliance degree on subjective cognizance, lack of determining basis for weighted coefficient, lacking post analysis and so on. Considering the above deficiencies, this paper adopts DEA method to establish multi-objective comprehensive evaluation model coupling period and robustness of underground powerhouse construction simulation. Next, comparative validity analysis and scheme evaluation of optimal scheme obtained with genetic algorithm is made. Finally, projection theorem is used to analyze the failure cause of other invalidation schemes. The research conducted provides theoretical support for construction organization design and decision making in project management. |