改进遗传算法的导弹目标分配方法

针对遗传算法在解决导弹目标分配问题中的困难,将火力单位的目标分配问题变换为针对导弹的目标分配问题,之后应用遗传算法求解,求解后还原为火力单位的分配结果,并用实例验证了应用遗传算法的可行性.之后,引入"优势"基因对标准遗传算法进行改进,大量实例表明,改进后的算法提高约60%的搜索效率.     

基于BP神经网络的D-S证据理论及其应用

命题基本概率分配(BPA)的确定是D-S证据理论得以广泛应用的关键之一.目前,大部分确定方法受专家知识偏好影响较大,难以反映客观情况.将BP网络运用到基本概率分配的确定过程中,使得BP网络和D-S证据理论两者有机地联合应用,这样既可利用D-S证据理论来表达和处理不确定信息,又可以充分发挥BP网络的自学习、自适应和容错能力.文中建立了基于BP网络的D-S证据理论的故障诊断模型,并给出了证据的融合算法.仿真实验表明,该模型可行.     

地面防空火力单元抗饱和攻击能力分析与应用

在分析影响防空火力单元抗饱和攻击能力的基础上,建立了基于排队论求解防空作战能力的数学模型,对防空火力单元的抗饱和攻击能力进行了仿真计算。通过对火力单元对目标射击的毁歼概率和服务时间相对于抗击率的相互关系的分析,研究了集火射击对于防空兵群抗饱和攻击能力的影响,并在兵力资源需求分析和防空火力配系优化等方面进行了运用。     

弹炮结合武器系统火力分配优化问题研究

在确定弹炮结合武器系统对目标的可射击系数、火力重叠修正系数和转火矛盾修正系数的基础上,结合防空作战的实际,通过对运用地空导弹射击、运用高炮射击、运用地空导弹和高炮混合射击三种情况的分析,介绍了解决弹炮结合武器系统火力分配优化问题的一般步骤。通过算例,证明了该方法的可行性,为有效解决弹炮结合武器系统火力分配优化问题提供了一种较为科学的方法。     

舰空导弹武器系统转火射击能力研究

讨论了舰空导弹武器系统转火射击的概念,分析了影响转火射击能力的主要因素,提出了舰空导弹武器系统射击周期、最大射击周期、最小射击周期概念,并对其数学模型进行了详细分析。     

舰空导弹协同攻击目标分配方法研究

根据双舰编队反导队形的配置和舰空导弹的战术技术性能,提出了针对多批目标的实时火力分配决策方法,根据当前态势和火力单元特性对需分配的目标进行静态实时火力分配,系统不断循环直至目标分配完毕,最后用实例进行了分析,计算结果表明了该方法的有效性.     

瓶颈指派问题的一种多项式时间算法

本文对瓶颈指派问题给出了一种新的算法,该算法不需要利用最大流算法,而类似于解经典指派问题的匈牙利算法。该算法是一个多项式时间算法,其复杂性为Ｏ（ｎ３）     

Bicriteria multiresource generalized assignment problem

In this study, we consider a bicriteria multiresource generalized assignment problem. Our criteria are the total assignment load and maximum assignment load over all agents. We aim to generate all nondominated objective vectors and the corresponding efficient solutions. We propose several lower and upper bounds and use them in our optimization and heuristic algorithms. The computational results have shown the satisfactory behaviors of our approaches. © 2014 Wiley Periodicals, Inc. Naval Research Logistics, 61: 621–636, 2014     

Graph distance‐dependent labeling related to code assignment in computer networks

For nonnegative integers d₁, d₂, and L(d₁, d₂)‐labeling of a graph G, is a function f : V(G) → {0, 1, 2, …} such that |f(u) − f(v)| ≥ d_i whenever the distance between u and v is i in G, for i = 1, 2. The L(d₁, d₂)‐number of G, λ(G) is the smallest k such that there exists an L(d₁, d₂)‐labeling with the largest label k. These labelings have an application to a computer code assignment problem. The task is to assign integer “control codes” to a network of computer stations with distance restrictions, which allow d₁ ≤ d₂. In this article, we will study the labelings with (d₁, d₂) ∈ {(0, 1), (1, 1), (1, 2)}. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Exact algorithms and bounds for the dynamic assignment interdiction problem

We study a multi‐stage dynamic assignment interdiction (DAI) game in which two agents, a user and an attacker, compete in the underlying bipartite assignment graph. The user wishes to assign a set of tasks at the minimum cost, and the attacker seeks to interdict a subset of arcs to maximize the user's objective. The user assigns exactly one task per stage, and the assignment costs and interdiction impacts vary across stages. Before any stage commences in the game, the attacker can interdict arcs subject to a cardinality constraint. An interdicted arc can still be used by the user, but at an increased assignment cost. The goal is to find an optimal sequence of assignments, coupled with the attacker's optimal interdiction strategy. We prove that this problem is strongly NP‐hard, even when the attacker can interdict only one arc. We propose an exact exponential‐state dynamic‐programming algorithm for this problem as well as lower and upper bounds on the optimal objective function value. Our bounds are based on classical interdiction and robust optimization models, and on variations of the DAI game. We examine the efficiency of our algorithms and the quality of our bounds on a set of randomly generated instances. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 373–387, 2017