改进人工蜂群算法的无人机航迹规划研究

如何快速地规划出满足约束条件的飞行航迹,是实现无人机自主飞行的关键。将改进的人工蜂群算法应用于求解无人机航迹规划问题,同时在人工蜂群算法的侦察阶段引入差分进化算法的思想。通过仿真实验并与标准人工蜂群算法比较,结果表明此算法能够有效加快收敛速度,提高最优航迹精度,是解决航迹规划和其他高维复杂函数优化的有效方法。     

管道机器人在三通处的通过性分析

三通是管道机器人经常遇到的典型障碍之一,克服该障碍的能力用管道机器人在三通处通过性来描述。文中提出一种描述差压驱动式管道机器人三通通过性的数学模型,该模型由一组组合约束构成。通过对约束方程的分析讨论、与管道机器人弯道通过性的对比分析,得出了规律性的结论。管道机器人在三通处的姿态、单元体的几何尺寸、行走轮结构形式对其通过性都有不同程度的影响。所提出数学模型是管道机器人三通自主行走控制策略设计和相应结构设计的理论基础。     

不完全信息的装备采购博弈

目前,我国的军品市场正由封闭市场向一个相对开放竞争的环境转变。基于不完全信息的装备采购的博弈模型,探讨了在不完全信息的相对开放的竞争环境下,军企双方对对方的策略、偏好、所处的地位或者状态的信息等策略问题进行了解,并给出了求解方法,通过实例进行了说明,对装备采购实践具有一定的指导意义。     

拦截高速机动目标的捕获区及微分对策导引律

针对高速机动目标拦截场景,研究末制导段捕获区存在条件及微分对策导引律问题。建立弹目相对运动模型并引入控制动力学模型,采用终端投影方法对相对运动模型进行降阶处理;基于微分对策理论推导一种解析形式捕获区,并具体到直/气复合控制导弹对机动目标的拦截中,该捕获区的存在能够保证对任意机动目标进行准确捕获;重新选取性能指标,将目标与直/气复合控制导弹在末端带有碰撞角约束的制导问题转化为零和微分对策问题,并求解出弹目最优拦截策略。仿真分析了几种情形下直/气复合控制导弹对目标实施拦截的捕获区存在域,导引律仿真结果表明微分对策导引律在对高速机动目标进行拦截时具有优良性能。     

An improved adaptive differential evolution algorithm for single unmanned aerial vehicle multitasking

Single unmanned aerial vehicle (UAV) multitasking plays an important role in multiple UAVs cooperative control, which is as well as the most complicated and hardest part. This paper establishes a three-dimensional topographical map, and an improved adaptive differential evolution (IADE) algorithm is proposed for single UAV multitasking. As an optimized problem, the efficiency of using standard differential evolution to obtain the global optimal solution is very low to avoid this problem. Therefore, the algorithm adopts the mutation factor and crossover factor into dynamic adaptive functions, which makes the crossover factor and variation factor can be adjusted with the number of population iteration and individual fitness value, letting the algorithm exploration and development more reasonable. The experimental results implicate that the IADE algorithm has better performance, higher convergence and efficiency to solve the multitasking problem compared with other algorithms.     

A search game on a cyclic graph

There is a finite cyclic graph. The hider chooses one of all nodes except the specified one, and he hides an (immobile) object there. At the beginning the seeker is at the specified node. After the seeker chooses an ordering of the nodes except the specified one, he examines each nodes in that order until he finds the object, traveling along edges. It costs an amount when he moves from a node to an adjacent one and also when he checks a node. While the hider wishes to maximize the sum of the traveling costs and the examination costs which are required to find the object, the seeker wishes to minimize it. The problem is modeled as a two‐person zero‐sum game. We solve the game when unit costs (traveling cost + examination cost) have geometrical relations depending on nodes. Then we give properties of optimal strategies of both players. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Market entry strategy in the presence of market spillovers and efficiency differentiation

Firms form various alliances or use brand extensions to enter new markets in order to improve their operational efficiency and create a positive spillover. However, they do not always know the implications of these strategies for market entry and multimarket competition because the sale of products in one market can have negative spillover effects on product sales in other markets. We present an analytical framework to examine whether and how (i.e., by choosing alliance entry or independent entry) competing firms should enter a market in a situation where market spillovers occur when a firm enters a spillover-producing market to sell products that may increase or decrease the consumers' willingness to pay for products in the primary market. Our analysis shows that the operational efficiency (or quality differentiation ability) of firms in a spillover-producing market varies, and hence, the impact of market spillovers differs for firms. We identify the key factors, such as bargaining power, brand value difference in the primary market, and the extent of efficiencies and spillovers, that determine the firms benefitting from the different entry strategies. Specifically, we show that firms would be more willing to choose an alliance strategy to enter a spillover-producing market if the negative spillover is small and alliance efficiency is high. In contrast, if an alliance entry is not favored, the firms' relative operational efficiency is crucial for them to decide whether to enter the market independently under moderate spillover conditions. Finally, we show the implications of market entry strategies for managers.     

含非线性半群的微分包含

研究了形如X＇（t）∈-Ax（t）＋F（t,x（t））,0≤t≤T,X（0）＝x0的微分包含解的存在的局部性和整体性的结果,并在某种条件下研究了解的稳定性。     

Constrained minimax optimization of continuous search efforts for the detection of a stationary target

Analytical resolution of search theory problems, as formalized by B.O. Koopman, may be applied with some model extension to various resource management issues. However, a fundamental prerequisite is the knowledge of the prior target density. Though this assumption has the definite advantage of simplicity, its drawback is clearly that target reactivity is not taken into account. As a preliminary step towards reactive target study stands the problem of resource planning under a min–max game context. This paper is related to Nakai's work about the game planning of resources for the detection of a stationary target. However, this initial problem is extended by adding new and more general constraints, allowing a more realistic modeling of the target and searcher behaviors. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Technical note: Find a hidden “treasure”

This paper deals with a two searchers game and it investigates the problem of how the possibility of finding a hidden object simultaneously by players influences their behavior. Namely, we consider the following two‐sided allocation non‐zero‐sum game on an integer interval [1,n]. Two teams (Player 1 and 2) want to find an immobile object (say, a treasure) hidden at one of n points. Each point i ∈ [1,n] is characterized by a detection parameter λ_i (μ_i) for Player 1 (Player 2) such that p_i(1 ? exp(?λ_ix_i)) (p_i(1 ? exp(?μ_iy_i))) is the probability that Player 1 (Player 2) discovers the hidden object with amount of search effort x_i (y_i) applied at point i where p_i ∈ (0,1) is the probability that the object is hidden at point i. Player 1 (Player 2) undertakes the search by allocating the total amount of effort X(Y). The payoff for Player 1 (Player 2) is 1 if he detects the object but his opponent does not. If both players detect the object they can share it proportionally and even can pay some share to an umpire who takes care that the players do not cheat each other, namely Player 1 gets q₁ and Player 2 gets q₂ where q₁ + q₂ ≤ 1. The Nash equilibrium of this game is found and numerical examples are given. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007