Adjacency‐based local top‐down search method for finding maximal efficient faces in multiple objective linear programming

It is well‐known that the efficient set of a multiobjective linear programming (MOLP) problem can be represented as a union of the maximal efficient faces of the feasible region. In this paper, we propose a method for finding all maximal efficient faces for an MOLP. The new method is based on a condition that all efficient vertices (short for the efficient extreme points and rays) for the MOLP have been found and it relies on the adjacency, affine independence and convexity results of efficient sets. The method uses a local top‐down search strategy to determine maximal efficient faces incident to every efficient vertex for finding maximal efficient faces of an MOLP problem. To our knowledge, the proposed method is the first top‐down search method that uses the adjacency property of the efficient set to find all maximal efficient faces. We discuss this and other advantages and disadvantages of the algorithm. We also discuss some computational experience we have had with our computer code for implementing the algorithm. This computational experience involved solving several MOLP problems with the code.     

不完全权重信息下地空导弹部队阵地评价与排序

给出了地空导弹部队阵地评价指标体系,在已知专家对各指标的打分结果和目标权重范围的局部信息基础下,提出一种先进行局部优化再组合赋权以求得指标的组合权重向量,并根据综合属性值对各方案进行排序的多目标决策方法,避免了获取有关地空导弹部队评价指标偏好信息的困难,最后以实例说明了本方法的应用情况.     

武器系统综合效能模糊识别模型

武器系统的综合性能评价是一个半结构型多目标决策问题,引入指标相对隶属度概念,提出了一种新的指标权重确定方法,并综合模糊优选、模糊识别等理论建立了武器系统的多级模糊识别模型。示例对三型反舰导弹武器系统效能进行模糊识别,得到其性能相对客观的评估。     

Modeling and analysis of multiobjective lot splitting for N‐product M‐machine flowshop lines

Lot splitting is a new approach for improving productivity by dividing production lots into sublots. This approach enables accelerating production flow, reducing lead‐time and increasing the utilization of organization resources. Most of the lot splitting models in the literature have addressed a single objective problem, usually the makespan or flowtime objectives. Simultaneous minimization of these two objectives has rarely been addressed in the literature despite of its high relevancy to most industrial environments. This work aims at solving a multiobjective lot splitting problem for multiple products in a flowshop environment. Tight mixed‐integer linear programming (MILP) formulations for minimizing the makespan and flowtime are presented. Then, the MinMax solution, which takes both objectives into consideration, is defined and suggested as an alternative objective. By solving the MILP model, it was found that minimizing one objective results in an average loss of about 15% in the other objective. The MinMax solution, on the other hand, results in an average loss of 4.6% from the furthest objective and 2.5% from the closest objective. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于MOEA/D的航天器隔振器多目标优化方法研究

由于存在各种高频内部扰动,高精度航天器通常需要进行隔振设计,而被动隔振装置被广泛采用。在被动隔振装置设计中,抑制共振响应峰和隔离中高频振动存在很强的冲突性,需要进行多目标优化设计。首先,建立了隔振系统的动力学模型,提出了以传递函数共振峰幅值和中高频衰减为目标函数的多目标优化模型;其次,提出了基于分解的多目标进化算法（MOEA/D）对单级和两级级隔振装置进行多目标优化的设计方法;最后,对某空间隔振装置进行了数值仿真,结果验证了本文算法的有效性。     

带有活动收益不确定特征的成像侦察卫星调度问题

根据区域目标的侦察需求,研究了面向区域目标的多星调度问题。分析了调度问题中活动收益不确定特征,讨论了活动收益的上下界。针对收益不确定的特点,设计了影响力指标用于评估活动对调度方案的影响。基于活动影响力与执行时间设计了一种带局部诱导的禁忌搜索算法,采用分层次的、变评价函数机制引导求解过程趋向多目标优化,在优先提高覆盖率的同时兼顾减少资源消耗。最后,以算例验证了算法的有效性,并通过方案比较说明算法具有较好的寻优能力。     

An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations

Unmanned aerial vehicles (UAVs), increasingly vital to the success of military operations, operate in a complex and dynamic environment, sometimes in concert with manned aircraft. We present an extensible modeling framework for the solution to the dynamic resource management (DRM) problem, where airborne resources must be reassigned to time‐sensitive tasks in response to changes in battlespace conditions. The DRM problem is characterized by diverse tasks with time windows, heterogeneous resources with fuel‐ and payload‐capacity limitations, and multiple competing objectives. We propose an integer linear programing formulation for this problem, where mathematical feasibility is guaranteed. Although motivated by airborne military operations, the proposed general modeling framework is applicable to a wide array of settings, such as disaster relief operations. Additionally, land‐ or water‐based operations may be modeled within this framework, as well as any combination of manned and unmanned vehicles. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于模糊多目标对策的雷达反干扰策略优化

考虑到单部雷达反干扰效能评估指标多样化、模糊且存在不同权重的情况,在对策论基础上提出了一种雷达反干扰策略优化模型,并在考虑局中人偏好情况下,设计了一种模糊多目标对策最优混合策略求解算法,为找出较优化的雷达反干扰策略以及为战场决策提供参考。     

分布式遗传模拟退火算法的火力打击目标分配优化

根据火力打击规则,建立了多目标函数的目标分配模型,提出了分布式遗传模拟退火算法对模型进行求解。分布式遗传模拟退火算法基于经典遗传算法进行改进:将单目标串行搜索方式变成多目标分布式搜索方式,适用于多目标寻优问题求解;采用保留最优个体和轮盘赌相结合的方式进行个体选择,在交叉算子中引入模拟退火算法,使用自适应变异概率,较好地保持算法广度和深度搜索平衡。最后,通过仿真实验验证了算法的有效性和可靠性。     

超燃冲压发动机二维进气道多级多目标优化设计方法

提出了超燃冲压发动机二维进气道的多级多目标设计方法。选择总压恢复系数、压升比和阻力系数为性能目标,引入多级设计概念,分别基于一维气动力学分析方法和计算流体力学方法,采用混合遗传算法对4楔角外压和2楔角内压混合压缩进气道进行了多级多目标优化设计,得到了问题的Pareto非劣解集。采用上述方法可以提升超燃冲压发动机进气道的设计水平,得到高性能的设计方案。