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     

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     

任务分配问题的对称群方法

探讨了无人飞行器(UAV)编队的任务分配问题。任务分配是UAV协同控制的基础,其解是任务区域内各任务的一个排列。求解UAV任务分配问题的有效方法是能在合理的计算时间内找到近似最优解的启发式算法。用对称群描述UAV任务分配的搜索空间,基于右乘运算构造搜索邻域。仿真结果验证了群论禁忌搜索算法的有效性。     

北斗卫星伪距信号质量评估及偏差校正

针对北斗卫星信号存在系统性伪距偏差的问题,从多路径角度评估北斗三频信号的质量,验证了该项偏差与卫星轨道类型、卫星仰角及信号频率有关。为消除这一系统性偏差的影响,采用连续分段线性函数建立北斗三频伪距偏差校正模型。与现有的改正模型所不同,所提模型不仅采用了更长时间范围内的北斗实测数据,更为重要的是它顾及了改正数的精度信息。基于动态精密单点定位的实验结果表明,采用所提方法修正后,接收机定位性能有明显提升。     

一种基于部分搜索的GNSS模糊度解算方法

为解决LAMBDA算法搜索策略效率不高的问题,提出了一种基于部分搜索的模糊度解算新方法。该方法的解算成功率接近LAMBDA算法,且只需对最后3维模糊度元素采取搜索策略。同时,通过合理设定搜索椭球的大小和搜索策略;大大提高了搜索效率。通过实验对该新算法与Bootraping算法、LAMBDA算法进行了比较分析,进一步验证了该新算法的有效性。     

求解CVRP问题的一种改进启发式蚁群算法

针对蚁群算法求解CVRP问题时收敛速度慢、求解质量不高的缺点,提出了一种改进启发式蚁群算法。该算法借鉴蚁群系统和基于排列的蚂蚁系统的优点设计信息素更新策略,既加强了对每次迭代最好解的利用,又避免了陷入局部最优;按一定比例使用基本方法和基于PFIH方法构造路径,扩大了算法的搜索空间;采用一种混合局部搜索算子,增强了算法局部寻优能力。实验结果表明,改进启发式蚁群算法可以大幅度减少车辆运行成本,具有较快的收敛速度。     

远程制导火箭子母弹对机场跑道毁伤研究

对机场跑道毁伤封锁是远程制导武器的重要任务,其毁伤判断的依据是最小升降窗口存在与否。采用Monte-Carlo方法对远程制导火箭子母弹打击机场跑道的炸点分布进行仿真模拟,提出了一种改进的搜索飞机起降最小升降窗口算法,并用该算法计算分析了远程制导火箭子母弹相关战技术因素对机场跑道毁伤的影响程度。计算结果表明改进算法计算封锁概率的值相对于区域搜索算法更加精确,研究结果对远程制导火箭子母弹的作战运用及进一步优化设计具有参考与实用价值。     

A learning tabu search for a truck allocation problem with linear and nonlinear cost components

The two‐level problem studied in this article consists of optimizing the refueling costs of a fleet of locomotives over a railway network. The goal consists of determining: (1) the number of refueling trucks contracted for each yard (truck assignment problem denoted TAP) and (2) the refueling plan of each locomotive (fuel distribution problem denoted FDP). As the FDP can be solved efficiently with existing methods, the focus is put on the TAP only. In a first version of the problem (denoted (P1)), various linear costs (e.g., fuel, fixed cost associated with each refueling, weekly operating costs of trucks) have to be minimized while satisfying a set of constraints (e.g., limited capacities of the locomotives and the trucks). In contrast with the existing literature on this problem, two types of nonlinear cost components will also be considered, based on the following ideas: (1) if several trucks from the same fuel supplier are contracted for the same yard, the supplier is likely to propose discounted prices for that yard (Problem (P2)); (2) if a train stops too often on its route, a penalty is incurred, which represents the dissatisfaction of the clients (Problem (P3)). Even if exact methods based on a mixed integer linear program formulation are available for (P1), they are not appropriate anymore to tackle (P2) and (P3). Various methods are proposed for the TAP: a descent local search, a tabu search, and a learning tabu search (LTS). The latter is a new type of local search algorithm. It involves a learning process relying on a trail system, and it can be applied to any combinatorial optimization problem. Results are reported and discussed for a large set of instances (for (P1), (P2), and (P3)), and show the good performance of LTS. © 2014 Wiley Periodicals, Inc. 62:32–45, 2015     

A sequential scheduling problem with impatient jobs

There are n customers that need to be served. Customer i will only wait in queue for an exponentially distributed time with rate λ_i before departing the system. The service time of customer i has distribution F_i, and on completion of service of customer i a positive reward r_i is earned. There is a single server and the problem is to choose, after each service completion, which currently in queue customer to serve next so as to maximize the expected total return. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 659–663, 2015     

基于GSPN的舰载服务器系统可靠性建模及分析

提出一种基于广义随机Petri网(Generalized Stochastic Petri Net,GSPN)的舰载服务器系统可靠性分析方法。深入分析舰载服务器系统故障模式的基础上,建立冗余服务器子系统的GSPN模型和共享数据盘子系统的GSPN模型,进而综合得到舰载服务器系统的全局GSPN模型,有效模拟了舰载服务器系统的动态行为。仿真实验验证了所提方法的有效性,为舰载服务器系统的分析与设计提供理论参考。