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This study designs a novel variable solidity Darrieus-type vertical axis wind turbine (D-VAWT) to solve the self-starting problem and optimize the aerodynamic performance. Two dynamic methods based on computational fluid dynamics are used to simulate different operation phases of the D-VAWT. Research results show that the solidity (σ) and moment of inertia (J z) have a greater effect on the self-starting capability. With the increase of σ, the self-starting capability increases. The D-VAWT with σ ≥ 0.417 can achieve self-starting with a starting-up time of fewer than 30s under the condition of 7.9 m/s incoming wind. Small solidity (σ = 0.417) D-VAWT has a wider tip speed ratio (λ) operating range and generates electricity stably under the generator load. The σ of the D-VAWT in the self-starting phase is 0.83 and in the power generation operation phase is 0.417. The maximum power coefficient （ C p ） is 0.342 with the optimal λ of 3.25. Compared with the fixed solidity (σ = 0.83) D-VAWT, the maximum power of a single D-VAWT increased from 53.42W to 100.39W to increase the maximum power by 188%. • A novel variable solidity Darrieus-type vertical axis wind turbine by changing the rotor radius is proposed. • This study improves the D-VAWT's self-starting capability. • The wind turbine has excellent aerodynamic performance at the power generation stage. • The D-VAWT has advantages in urban areas. [ABSTRACT FROM AUTHOR]

This study proposes a new approach to determine the dispatching rules of AGVs and container storage locations, considering both unloading and loading processes simultaneously. We formulate this problem as a mixed integer programming model, aiming to minimise the ship’s berth time. Optimal solutions can be obtained in small sizes, however, large-sized problems are hard to solve optimally in a reasonable time. Therefore, a heuristic method, i.e. genetic algorithm is designed to solve the problem in large sizes. A series of numerical experiments are carried out to evaluate the effectiveness of the integration approach and algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we study the optimization of yard operations, which are critical for the terminal efficiency. A linear mixed integer programming (MIP) model is proposed for scheduling different types of equipment and planning the storage strategy in an integrated way. We also investigate a nonlinear mixed integer programming (NLMIP) model to reduce the number of constraints and the computational time. A set of numerical results are carried out for the comparison between the linear model and the nonlinear model. Finally, we propose a genetic algorithm for the MIP model to illustrate how large scale problems can be solved and to show the effect of different factors on the performances of the optimization model. [Copyright &y& Elsevier]