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The neutron background spectrum from thermal neutron to 20 MeV fast neutron was measured at the first experimental hall of China Jinping underground laboratory with a Bonner multi-sphere spectrometer. The measurement system was validated by a 252 Cf source and inconformity was corrected. Due to micro charge discharge, the dataset was screened and background from the steel of the detectors was estimated by MC simulation. Based on genetic algorithm we obtained the energy distribution of the neutron and the total flux of neutron was (2.69±1.02) ×10 −5 cm −2 s −1 . [ABSTRACT FROM AUTHOR]

The aim of this article is to develop an antithetic method-based particle swarm optimization to solve a queuing network problem with fuzzy data for concrete transportation systems. The concrete transportation system at the Jinping-I Hydropower Project is considered the prototype and is extended to a generalized queuing network problem. The decision maker needs to allocate a limited number of vehicles and unloading equipment in multiple stages to the different queuing network transportation paths to improve construction efficiency by minimizing both the total operational costs and the construction duration. A multiple objective decision-making model is established which takes into account the constraints and the fuzzy data. To deal with the fuzzy variables in the model, a fuzzy expected value operator, which uses an optimistic-pessimistic index, is introduced to reflect the decision maker's attitude. The particular nature of this model requires the development of an antithetic method-based particle swarm optimization algorithm. Instead of using a traditional updating method, an antithetic particle-updating mechanism is designed to automatically control the particle-updating in the feasible solution space. Results and a sensitivity analysis for the Jinping-I Hydropower Project are presented to demonstrate the performance of our optimization method, which was proved to be very effective and efficient compared to the actual data from the project and other metaheuristic algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a resource sharing-based construction equipment allocation problem with multiple stages under a fuzzy environment. A multiobjective multistage decision-making model is established in which the equipment failure rate is regarded as a fuzzy variable. In contrast to traditional assignment problems, the principle of resource sharing modes including space and time sharing is considered to be based on the project practice. In addition, a dynamic programming-based genetic algorithm is developed to find feasible solutions and a dynamic programming-based initialization, and crossover and mutation are designed to avoid infeasible solutions. Finally, the Jinping-I Hydropower Project is used as a practical example to demonstrate the practicality and efficiency of the model. The comparisons and analysis of results are presented to highlight the performance of the optimization method, which is proved to be more effective and efficient than the standard genetic algorithm. [ABSTRACT FROM AUTHOR]