On efficient algorithms for finding efficient salvo policies

We consider the salvo policy problem, in which there are k moments, called salvos, at which we can fire multiple missiles simultaneously at an incoming object. Each salvo is characterized by a probability p_i: the hit probability of a single missile. After each salvo, we can assess whether the incoming object is still active. If it is, we fire the missiles assigned to the next salvo. In the salvo policy problem, the goal is to assign at most n missiles to salvos in order to minimize the expected number of missiles used. We consider three problem versions. In Gould's version, we have to assign all n missiles to salvos. In the Big Bomb version, a cost of B is incurred when all salvo's are unsuccessful. Finally, we consider the Quota version in which the kill probability should exceed some quota Q. We discuss the computational complexity and the approximability of these problem versions. In particular, we show that Gould's version and the Big Bomb version admit pseudopolynomial time exact algorithms and fully polynomial time approximation schemes. We also present an iterative approximation algorithm for the Quota version, and show that a related problem is NP-complete.     

Technical note: Finite-time regret analysis of Kiefer-Wolfowitz stochastic approximation algorithm and nonparametric multi-product dynamic pricing with unknown demand

We consider the problem of nonparametric multi-product dynamic pricing with unknown demand and show that the problem may be formulated as an online model-free stochastic program, which can be solved by the classical Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. We prove that the expected cumulative regret of the KWSA algorithm is bounded above by where κ₁, κ₂ are positive constants and T is the number of periods for any T = 1, 2, … . Therefore, the regret of the KWSA algorithm grows in the order of , which achieves the lower bounds known for parametric dynamic pricing problems and shows that the nonparametric problems are not necessarily more difficult to solve than the parametric ones. Numerical experiments further demonstrate the effectiveness and efficiency of our proposed KW pricing policy by comparing with some pricing policies in the literature.     

基于免疫粒子群算法的自抗扰飞行控制器设计

提出了一种基于免疫粒子群优化算法的自抗扰大包线飞行控制器设计方法.针对传统的增益调参设计方法存在的工作量巨大与设计效率低的问题,利用自抗扰控制器进行大包线飞行控制器设计,并推导了适用于该方法的飞机非线性方程.由于自抗扰控制能够动态补偿对象模型的内扰和外扰,因此在很大的飞行区域内仅需一套控制器便可,从而避免了烦琐复杂的增益调参设计过程,并用免疫粒子群优化算法对自抗扰控制器参数进行了优化研究.仿真结果表明,所设计的自抗扰控制器具有优良的控制性能,并且控制器参数在较大的包线范围内不需要改变,从而简化了大包线飞行控制器设计.     

The practice of strategy: South African defence in stasis

The article concerns the strategy development processes of the South African Department of Defence in South Africa. It intends to identify the probable causes of the observed failure of the South African National Defence Force to develop appropriate departmental policy and military strategy. Military strategy comprises force development, force employment, force deployment and the coordination of these elements in pursuit of national, grand-strategic objectives. (See Dennis M. Drew and Donald M. Snow, Making Twenty-first Century Strategy: An Introduction to Modern National Security Processes and Problems Montgomery, AL: Air University Press, Maxwell Air Force Base, November 2006, 103). Of these four constructs, the article concerns itself only with the first two. The article analyses two complementary approaches to strategy formation: a resource-driven, inside-out model and an interests-driven, outside-in method. The article concludes that the Department is preoccupied with the inside-out method to the lasting detriment of the declared strategic intent of the defence policy.     

云模型改进惯性权重的混沌交替粒子群算法

标准粒子群算法通过线性减小惯性权重系数来调整寻优性能,但缺乏智能化机制易导致算法后期产生早熟或陷入局部最优而产生僵局。针对这一问题,提出一种基于云模型改进惯性权重的混沌交替粒子群优化算法。根据粒子迭代变化关系,采用云模型理论对惯性权重ω进行智能化调整,以平衡其全局和局部搜索能力,防止算法产生局部僵局;另外,判定粒子稳定性,对于可能陷入局部僵局的稳定粒子进行混沌扰动,促使其跳出僵局进而向最优位置更新。实验与分析表明,基于云模型改进惯性权重的混沌交替粒子群优化算法能够跳出局部僵局且具有较高的寻优精度,算法接近完全收敛时的平均迭代次数,较现有相关研究分别降低了13.73%~20.11%。     

A Good Ally - Norway and International Statebuilding in Afghanistan, 2001-2014

The article examines the findings of the Commission of Inquiry established by the Norwegian government in 2014 to evaluate all aspects of Norway’s civilian and military contribution to the international operation in Afghanistan from 2001 to 2014. Concerned with the wider implications of the Commission’s findings, it focuses on two issues in particular: (1) Norway’s relations with the US, a close and long-standing strategic ally whose resources, capabilities and dominance of decision-making dwarfed that of all other coalition partners in Afghanistan; and (2) Norway’s record in the province of Faryab, where, from 2005 to 2012, a Norwegian-led Provincial Reconstruction Team was charged with bringing security, good governance and development to the province. How Norway prioritised and managed relations with the US highlights and helps to problematise the challenges – political, practical and moral – facing small and medium-sized powers operating in a coalition alongside the US. Norwegian efforts in Faryab are revealing of the dilemmas and contradictions that plagued and, ultimately, fatally undermined the international intervention as a whole. As such, Norway’s experience provides a microcosm through which the inherent limitations of the attempt to transfer the structures of modern statehood and Western democracy to Afghanistan can be better understood.     

What Is Known About Defence Research And Development Spill-Overs?

This article surveys the body of available evidence regarding the spill-over effects of defence R&D. It reviews the routes through which defence R&D spills over to the economy with positive externalities – in terms of new products, technologies or processes; the barriers that impede or block such a process; potential negative repercussions, and the measure of such effects. The main conclusion is that the uncertainty of these effects, and the inaccurate appraisal of their value, hardly supports informed decisions concerning defence R&D policies.     

合成分队双层主从决策模型研究

针对合成分队不同指挥层级之间的决策交互优化问题,提出了基于主从决策的双层武器目标分配模型。该模型能够体现上下指挥层级之间交互式决策协调优化的特点:上层目标为主攻方向我方遭受威胁最小,下层目标为对敌打击最大。结合合成分队作战决策的特点和要求,提出了一种求解该模型的改进型粒子群优化算法。仿真结果表明,该模型合理有效,改进的求解算法能够获得满意解。     

Dynamic inventory management with cash flow constraints

In this article, we consider a classic dynamic inventory control problem of a self‐financing retailer who periodically replenishes its stock from a supplier and sells it to the market. The replenishment decisions of the retailer are constrained by cash flow, which is updated periodically following purchasing and sales in each period. Excess demand in each period is lost when insufficient inventory is in stock. The retailer's objective is to maximize its expected terminal wealth at the end of the planning horizon. We characterize the optimal inventory control policy and present a simple algorithm for computing the optimal policies for each period. Conditions are identified under which the optimal control policies are identical across periods. We also present comparative statics results on the optimal control policy. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2008     

对高等教育若干问题的思考

目前高等教育中存在的种种弊端,迫使高等教育必须改革。高等教育决不能脱离党的教育方针,要强化世界观和价值观教育,远离社会不良风气的干扰,培养出德智体全面发展的人才。