再论线性多目标规划有效解的有效率

对文（1）中的优势集进行重新定义，讨论了非劣极点优势集的性质，在此基础上修正了文（1）中有效率的定义。     

公路网布局的多目标优化模型

针对现有公路网布局优化模型的目标函数过于偏重机动性的缺点,在公路网布局优化模型中引入了可达性的概念,建立了多目标双层优化模型.上层考虑建设资金的约束,以公路网可达性最大和交通负荷度最小为目标函数;下层与传统的4阶段交通规划模型相结合,采用用户均衡配流模型.为了反映上层模型的两个目标函数之间的trade-off关系,设计了基于Pareto最优的求解算法,并采用进化算法实现.文中提出的方法在北部湾区域公路网布局规划中得以运用.     

Wear/comfort Pareto optimisation of bogie suspension

Pareto optimisation of bogie suspension components is considered for a 50 degrees of freedom railway vehicle model to reduce wheel/rail contact wear and improve passenger ride comfort. Several operational scenarios including tracks with different curve radii ranging from very small radii up to straight tracks are considered for the analysis. In each case, the maximum admissible speed is applied to the vehicle. Design parameters are categorised into two levels and the wear/comfort Pareto optimisation is accordingly accomplished in a multistep manner to improve the computational efficiency. The genetic algorithm (GA) is employed to perform the multi-objective optimisation. Two suspension system configurations are considered, a symmetric and an asymmetric in which the primary or secondary suspension elements on the right- and left-hand sides of the vehicle are not the same. It is shown that the vehicle performance on curves can be significantly improved using the asymmetric suspension configuration. The Pareto-optimised values of the design parameters achieved here guarantee wear reduction and comfort improvement for railway vehicles and can also be utilised in developing the reference vehicle models for design of bogie active suspension systems.     

PHEV复合储能系统设计及基于MODA的参数优化

为了提高插电式混合动力汽车的燃油经济性、降低污染物的排放,并解决插电式混合动力汽车单一动力电池低比功率、无法响应暂态功率需求的问题,设计蓄电池和超级电容并联的复合储能系统,采用带有滑动窗口的实时小波功率分配策略,并对滑动窗口长度进行选择。该功率分配策略将复合储能系统的需求功率分解成高频和低频两部分,超级电容接收高频分量,蓄电池接收低频分量,避免了高频分量对于蓄电池的冲击,提高了蓄电池的耐久性和可靠性。制定基于规则的控制策略,以整车燃油消耗量和污染物排放量为优化目标,利用多目标蜻蜓算法对相关控制参数进行优化。基于ADVISOR搭建含有复合储能系统的插电式混合动力汽车整车仿真模型,采用新欧洲行驶循环工况进行测试,并通过与带精英策略的非支配排序遗传算法进行对比,验证算法的有效性。研究结果表明：利用多目标蜻蜓算法优化后的车辆百公里燃油消耗平均降低了12.71%,污染物综合排放性能平均下降了10.05%;相对于优化前,发动机输出功率减少,电机输出功率增加,发动机和电机的工作效率均得到了显著提升;Pareto最优解的收敛性和覆盖范围优于带精英策略的非支配排序遗传算法,同时得到的多组Pareto最优解为整车设计和优化提供了更多选择。     

Multi-objective optimization study on dimensions of medium-sized cruise ship in concept phase北大核心CSCD

［Objective］Aiming at the problem of too many influencing factors and too little reference data for determining the dimensions of medium-sized cruise ships in the concept phase, a simplified multi-objective optimization method based on the fitting of dimensions and performance is proposed. ［Method］First, the dimension relations of medium-sized cruise ships are analyzed and the influence of the latest SOLAS requirements used to determine the optimization range. Second, the influence of cruise ship dimensions on space, resistance, stability and seakeeping are analyzed. Next, based on the principles of genetic algorithms, a multiobjective optimization algorithm with high robustness and high engineering adaptability is determined to establish a multi-objective optimization model for the concept design of medium-sized cruise ships. Finally, the Pareto solution obtained by multi-objective optimization is analyzed to provide initial references for determining the dimensions of the target cruise ship. ［Results］Implemented via a genetic algorithm, the optimization program proposed herein is applied in the concept design of a medium-sized cruise ship in order to optimize the initial dimensions, thereby achieving the expected outcome of providing reasonable initial dimensions for cruise ship design. ［Conclusion ］ The proposed simplified multi-objective optimization model can provide feasible initial dimensions for medium-sized cruise ships in the concept phase. As the Pareto solution obtained by multi-objective optimization has different focuses such as resistance and stability, the most suitable solution needs to be selected according to the design object. © 2023 Chinese Journal of Ship Research. All rights reserved.