Multispacecraft refueling optimization considering the J2 perturbation and window constraints

The optimization of a near-circular low-Earth-orbit multispacecraft refueling problem is studied. The refueling sequence, service time, and orbital transfer time are used as design variables, whereas the mean mission completion time and mean propellant consumed by orbital maneuvers are used as design objectives. The J2 term of the Earth's nonspherical gravity perturbation and the constraints of rendezvous time windows are taken into account. A hybridencoding genetic algorithm, which uses normal fitness assignment to find the minimum mean propellant-cost solution and fitness assignment based on the concept of Pareto-optimality to find multi-objective optimal solutions, is presented. The proposed approach is demonstrated for a typical multispacecraft refueling problem. The results show that the proposed approach is effective, and that the J2 perturbation and the time-window constraints have considerable influences on the optimization results. For the problems in which the J2 perturbation is not accounted for, the optimal refueling order can be simply determined as a sequential order or as the order only based on orbitalplane differences. In contrast, for the problems that do consider the J2 perturbation, the optimal solutions obtained have a variety of refueling orders and use the drift of nodes effectively to reduce the propellant cost for eliminating orbital-plane differences. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.

Geometry parameter optimization of large cross-sectional S-shaped bent rib waveguides for silicon based optical switches

地址: Chinese Acad Sci, Inst Semicond, State Key Lab Integrated Optoelect, Beijing 100083, Peoples R China

基于路径共同顺序的TSP遗传算法

遗传算法是一种解决TSP问题的有效算法。文章提出了一种基于路径共同顺序的新型遗传操作方法,即首先寻找父辈的共有路径信息,然后构建后代,该方法缩小了搜索优解的范围,加快了优化过程的收敛速度。在此基础上针对TSP实例,实现了基于共同顺序的优化方法来解决小规模TSP问题,以及更有效的基于共同顺序的循环优化方法来解决大规模TSP问题。实验结果验证了该方法的有效性。

一种连续手写中文的演化分割方法

在连续手写中文中,有偏旁部首离得较远的单字,单字之间可能会存在粘连、重叠。针对这种情况给出了一种基于识别得分提取单字的演化方法。对行笔划序列进行二进制编码,采用改进的遗传算法实现演化过程。染色体中连续0或1对应的笔划组成候选单字。用汉王手写单字识别器获取它们的识别得分,以单字个数较少和总的识别得分较大为优化目标。遗传算法中的变异概率和交叉概率自适应生成。测试结果表明该方法对连续手写中文具有较好的分割效果。

Optimization and comparison of single- and dual-pump fiber-optical parametric amplifiers with dispersion fluctuations

Solutions for fiber-optical parametric amplifiers (FOPAs) with dispersion fluctuations are derived using matrix operators. On the basis of the propagation matrix product and the hybrid genetic algorithm, we have optimized and compared single- and dual-pump FOPAs with zero-dispersion-wavelength variations. The simulations prove that the design of FOPAs involves multimodal function optimization problems. The numerical results show that dual-pump FOPAs are highly sensitive to dispersion fluctuations whereas dispersion variations have less impact on the gain of single-pump FOPAs. To increase signal gain and reduce ripple, dual-pump FOPAs, instead of single-pump FOPAs, have to be carefully optimized with a suitable multisegment fiber structure rather than a one-segment fiber structure. The different combinations of multisegment fibers can provide highly different gain properties. The increase in gain is at the cost of the ripple.

Design optimization of the APF DTL in the SSC-linac

A linear accelerator as a new injector for the SSC (Separated Sector Cyclotron) of the HIRFL (Heavy ton Research Facility Lanzhou) is being designed. The DTL (Drift-Tube-Linac) has been designed to accelerate U-238(34+) from 0.140 MeV/u to 0.97 MeV/u. To the first accelerating tank which accelerates U-238(34+) to 0.54 MeV/u, the approach of Alternating-Phase-Focusing (APF) is applied. The phase array is obtained by coupling optimization software Dakota and beam optics code LINREV. With the hybrid of Multi-objective Genetic Algorithm (MOGA) and a pattern search method, an optimum array of asynchronous phases is determined. The final growth, both transversely and longitudinally, can meet the design requirements. In this paper, the deign optimization of the APF DTL is presented.

Design of silicone rubber according to requirements based on the multi-objective optimization of chemical reactions

The explicit expression between composition and mechanical properties of silicone rubber was derived from the physics of polymer elasticity, the implicit expression among material composition, reaction conditions and reaction efficiency was obtained from chemical thermodynamics and kinetics, and then an implicit multi-objective optimization model was constructed. Genetic algorithm was applied to optimize material composition and reaction conditions, and the finite element method of cross-linking reaction processes was used to solve multi-objective functions, on the basis of which a new optimization methodology of crosslinking reaction processes was established. Using this methodology, rubber materials can be designed according to pre-specified requirements.

Quantitative structure-property relationship research to the analysis of photoionization sensitivity of organic compounds in gas chromatography

The A(m) index and molecular connectivity index were used for studying the photoionization sensitivity of some organic compounds in gas chromatography. The analysis of structure-property relationship between the photoionization sensitivity of the compounds and the A(m) indices or molecular connectivity indices has been carried out. The genetic algorighm was used to build the correlation model in this field. The results demonstrate that the property of compounds can be described by both A(m) indices and molecular connectivity indices, and the mathematical model obtained by the genetic algorithm was better than that by multivariate regression analysis.

一种基于遗传算法的机器人加工路径规划方法

针对传统机器人加工路径规划采用示教再现方法很难适应复杂变化任务的问题 ,提出了基于遗传算法的路径规划方法 ,研究了遗传算法中的编码方式、交叉算子和变异算子的改进方法 .仿真实验表明 ,采用遗传算法进行机器人加工路径规划是可行的和有效的 .

基于最小疼痛感的机器人操作臂轨迹规划方法

针对机器人操作臂跟踪运动目标的问题,从仿生学的角度提出一种新的轨迹规划方法。将关节加速度的增量进行编码,同时将疼痛感作为优化指标,利用遗传算法在操作臂的关节空间进行轨迹优化,得到操作臂在跟踪运动目标过程中的具有较小疼痛感的轨迹。仿真试验结果表明,所提出的方法是可行的,可以规划出正确的跟踪轨迹,同时有效的减小了操作臂运动过程中的疼痛感。

基于多种群遗传算法的波能装置的优化设计及分析

作为可再生能源,波浪能的吸收和利用一直是国内外热点研究内容之一。本文提出一种新的基于惯性摆结构的波浪能吸收转换方法,对这种结构在波浪力作用下的频域响应进行了分析,建立了其最优化能量获取模型,提出采用多种群遗传算法对其结构进行优化设计,并针对系统所受波浪力(矩)随载体半径改变而改变,且求取困难的问题,采用最小二乘法对波浪力(矩)与载体半径变化的关系进行了拟和。通过优化结果找出影响结构获取波浪能量的因素,仿真结果表明了方法的先进性,为进一步的应用研究和频域波能获取研究奠定了基础。

机器人操作臂跟踪动态目标的轨迹规划方法

针对机器人操作臂跟踪运动目标问题,提出一种基于遗传算法的轨迹规划方法。通过对关节加速度的增量进行编码,实现在操作臂的关节空间进行轨迹优化,得到操作臂在跟踪运动目标过程中所需要的轨迹。仿真计算的结果表明,所提出的方法是有效的。

轮式移动机器人轨迹跟踪的最优控制

深入分析了轮式移动机器人的运动状态,建立了WMR路径偏差系统的非线性数学模型。应用小偏差线性化理论,将该多输入多输出非线性系统简化成一个单输入单输出线性系统。然后基于线性二次型调节器理论进行了系统最优控制器的设计,并针对该理论中加权矩阵Q与R难以确定的问题,从控制效果出发,采用自适应遗传算法对其进行了优化。实现了移动机器人对预定轨迹的满意鲁棒跟踪,同时满足了实时性要求。实验结果证明了该方法的正确性与实用性。

求解TSP问题的贪心遗传算法

提出贪心遗传算法。通过构建“基因库”形成好的“基因片断”,从而生成高性能的初始种群;依据贪心选择的原则指导遗传操作,实施贪心交叉操作和贪心变异操作;移民操作向种群引进新的遗传物质,克服了封闭竞争缺点,并且可以避免早熟收敛。贪心遗传算法可以大大加快搜索的速度,仿真结果表明算法是十分有效和实用的。