Trajectory Optimization Design for Morphing Wing Missile

This paper presents a new particle swarm optimization (PSO) algorithm to optimize the trajectory of morphing-wing missile so as to achieve the enlargement of the maximum range. Equations of motion for the two-dimensional dynamics are derived by treating the missile as an ideal controllable mass point. An investigation of aerodynamic characteristics of morphing-wing missile with varying geometries is performed. After deducing the optimizing trajectory model for maximizing range, a type of discrete method is put forward for taking optimization control problem into nonlinear dynamic programming problem. The optimal trajectory is solved by using PSO algorithm and penalty function method. The simulation results suggest that morphing-wing missile has the larger range than the fixed-shape missile when launched at supersonic speed, while morphing-wing missile has no obvious range increment than the fixed-shape missile at subsonic speed.     

On the Range of the Common Cycle Time in a Road Network

In a coordinated road network, the optimal common cycle time is determined by evaluating the performance of the network in the given range of cycles. Normally, this range is determined by users’ experience. And a large range of common cycle time, e.g. \[0,0\] is chosen, which requires long computation time. This study considers that the optimal common cycle time ranges between the minimal and maximal value of intersections’ individual optimal cycle time. It is proved mathematically from the convexity condition, that the delay of the network and each individual intersection are convex functions of the cycle time according to Webster delay model. Finally, 2 000 random cases for the network composed of two intersections and of eight intersections are created to underline the proposed conclusions. The results of all cases confirm the validity, and show up to 90% improvement in computation time to compare with experience range. The signal optimization tool, Synchro, is also used to validate the conclusion by 50 random cases. The results confirm reliability further.     

Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

As the number of objectives increases, the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization (EMO) algorithms such as NSGA-II, SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's (DM) preference information. This is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two, three, and four-objective knapsack problems. The results demonstrate the algorithm's ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition, the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.     

Effect of Cultural Conditions on Chitinase Production from Biocontrol Bacterium Against Aflatoxin

Chitinase is one of the most important mycolytic enzymes with industrial significance. Statistical methods are employed to optimize cultural conditions with the increased production of chitinase for th...     

Hydraulic Self Servo Swing Cylinder Structure Optimization and Dynamic Characteristics Analysis Based on Genetic Algorithm

The dynamic characteristics of hydraulic self servo swing cylinder were analyzed according to the hydraulic system natural frequency formula. Based on that, a method of the hydraulic self servo swing cylinder structure optimization based on genetic algorithm was proposed in this paper. By analyzing the four parameters that affect the dynamic characteristics, we had to optimize the structure to obtain as larger the Dm(displacement) as possible under the condition with the purpose of improving the dynamic characteristics of hydraulic self servo swing cylinder. So three state equations were established in this paper. The paper analyzed the effect of the four parameters in hydraulic self servo swing cylinder natural frequency equation and used the genetic algorithm to obtain the optimal solution of structure parameters. The model was simulated by substituting the parameters and initial value to the simulink model. Simulation results show that: using self servo hydraulic swing cylinder natural frequency equation to study its dynamic response characteristics is very effective. Compared with no optimization, the overall system dynamic response speed is significantly improved.     

Grid-Based Path Planner Using Multivariant Optimization Algorithm

To solve the shortest path planning problems on grid-based map efficiently, a novel heuristic path planning approach based on an intelligent swarm optimization method called Multivariant Optimization Algorithm (MOA) and a modified indirect encoding scheme are proposed. In MOA, the solution space is iteratively searched through global exploration and local exploitation by intelligent searching individuals, who are named as atoms. MOA is employed to locate the shortest path through iterations of global path planning and local path refinements in the proposed path planning approach. In each iteration, a group of global atoms are employed to perform the global path planning aiming at finding some candidate paths rapidly and then a group of local atoms are allotted to each candidate path for refinement. Further, the traditional indirect encoding scheme is modified to reduce the possibility of constructing an infeasible path from an array. Comparative experiments against two other frequently use intelligent optimization approaches: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are conducted on benchmark test problems of varying complexity to evaluate the performance of MOA. The results demonstrate that MOA outperforms GA and PSO in terms of optimality indicated by the length of the located path.     

一种应用于堆垛式立体车库AC-TSP算法的研究

针对堆垛式立体车库长期以来存取车所出现耗时长,能耗高等问题,本文采用一种AC-TSP(蚁群旅行商)算法进行优化,并应用于车库路径寻优来解决以上问题.通过对车库结构和存取车需求的分析,结合AC-TSP算法,建立简化的车库AC-TSP数学模型,把要存取车位置输入到工业计算机,经AC-TSP算法的快速计算,输出存取车的最优路径.经MATLAB仿真和实验得出存取车的所走路径的平均距离和最短距离,与实际的顺次存取车方法相比表明,该算法在存取车效率和节能等方面具有明显的优势.     

能量有效的频谱感知与接入策略联合优化算法

针对认知无线电网络中次用户节点能量受限问题,提出了一种联合考虑频谱感知和接入策略的能量有效优化算法。根据主用户非时隙接入信道可能与次用户发生碰撞的特点,基于连续时间马尔科夫理论对次用户的频谱感知和接入策略进行建模,在满足碰撞概率约束的条件下,通过合理设置次用户的感知时间和接入概率实现了感知性能与传输能效的有效折衷。仿真结果表明,相对于仅考虑感知时间或接入概率的传统优化算法,所提算法可使次用户的能量有效性得到显著提高。     

不确定载荷下刚架体结构稳健优化设计

针对工程结构承受扰动载荷难以准确获得的问题,开展对刚架体结构稳健优化设计方法研究。根据结构载荷响应以及不确定载荷边界的波动幅度,引入Information-Gap理论量化处理不确定参量。以结构应力约束为边界条件构建稳健函数,将结构能容许不确定载荷最大波动幅度作为评价结构的稳健性指标,构造稳健性函数最大化为目标的优化模型,为了克服求解上的困难,构造半定规划的形式对优化模型求解。通过数值仿真算例验证稳健性优化模型的有效性和可行性,通过优化前后结果对比,表明该方法能提高优化效率,更好发挥结构潜能,增强结构抵抗不确定载荷的能力,达到提高稳健性目的。     

火电机组主蒸汽流量在线监测计算方法

火电机组主蒸汽流量的准确测量,对于机组的经济性分析和节能降耗工作具有重要的价值。提供了一种基于平均影响值的多因素权重系数分配方法,并结合实际运行数据建立了主蒸汽流量的精确在线计算模型。对比了常规的支持向量机模型(SVR)、遗传算法优化的支持向量机模型(GAO-SVR)以及基于平均影响值进行权重系数分配及遗传算法优化的支持向量机(MIVW-GAO-SVR)模型的计算精度。验证结果表明了基于平均影响值多因素权重分配方法的有效性及MIVW-GAO-SVR主蒸汽流量监测模型的高精度性。