A dynamic gradient approach to Pareto optimization with nonsmooth convex objective functions

In a general Hilbert framework, we consider continuous gradient-like dynamical systems for constrained multiobjective optimization involving nonsmooth convex objective functions. Based on the Yosida regularization of the subdifferential operators involved in the system, we obtain the existence of strong global trajectories. We prove a descent property for each objective function, and the convergence of trajectories to weak Pareto minima. This approach provides a dynamical endogenous weighting of the objective functions, a key property for applications in cooperative games, inverse problems, and numerical multiobjective optimization.     

On Nash approximation of complex analytic sets in Runge domains

We prove that every complex analytic set X in a Runge domain Ω   can be approximated by Nash sets on any relatively compact subdomain _Ω0${\Omega }_0$ of Ω. Moreover, for every Nash subset Y of Ω   with Y⊂X$Y\subset X$, the approximating sets can be chosen so that they contain Y∩_Ω0$Y\cap {\Omega }_0$. As a consequence, we derive a necessary and sufficient condition for a complex analytic set X to admit a Nash approximation which coincides with X along its arbitrary given subset.     

A Minty variational principle for set optimization

Extremal problems are studied involving an objective function with values in (order) complete lattices of sets generated by so-called set relations. Contrary to the popular paradigm in vector optimization, the solution concept for such problems, introduced by F. Heyde and A. Löhne, comprises the attainment of the infimum as well as a minimality property. The main result is a Minty type variational inequality for set optimization problems which provides a sufficient optimality condition under lower semicontinuity assumptions and a necessary condition under appropriate generalized convexity assumptions. The variational inequality is based on a new Dini directional derivative for set-valued functions which is defined in terms of a “lattice difference quotient.” A residual operation in a lattice of sets replaces the inverse addition in linear spaces. Relationships to families of scalar problems are pointed out and used for proofs. The appearance of improper scalarizations poses a major difficulty which is dealt with by extending known scalar results such as Diewert's theorem to improper functions.     

Uncertain multiobjective traveling salesman problem

Traveling salesman problem is a fundamental combinatorial optimization model studied in the operations research community for nearly half a century, yet there is surprisingly little literature that addresses uncertainty and multiple objectives in it. A novel TSP variation, called uncertain multiobjective TSP (UMTSP) with uncertain variables on the arc, is proposed in this paper on the basis of uncertainty theory, and a new solution approach named uncertain approach is applied to obtain Pareto efficient route in UMTSP. Considering the uncertain and combinatorial nature of UMTSP, a new ABC algorithm inserted with reverse operator, crossover operator and mutation operator is designed to this problem, which outperforms other algorithms through the performance comparison on three benchmark TSPs. Finally, a new benchmark UMTSP case study is presented to illustrate the construction and solution of UMTSP, which shows that the optimal route in deterministic TSP can be a poor route in UMTSP.     

汽车租赁调度多目标优化模型

本文考虑一个周期的汽车租赁调度问题,在直接调运的前提下,首先以汽车租赁公司的总收益最大和总短缺损失最小为目标,建立多目标优化模型;然后提出了基于启发式的双层排序综合择优算法;最后对汽车租赁案例进行了实证研究。     

线性半向量二层规划问题的全局优化方法

研究了线性半向量二层规划问题的全局优化方法. 利用下层问题的对偶间隙构造了线性半向量二层规划问题的罚问题, 通过分析原问题的最优解与罚问题可行域顶点之间的关系, 将线性半向量二层规划问题转化为有限个线性规划问题, 从而得到线性半向量二层规划问题的全局最优解. 数值结果表明所设计的全局优化方法对线性半向量二层规划问题是可行的.     

基于车身装配结构优化的改进图分解算法

在考虑车身制造和装配成本的前提下对车身装配结构优化方法进行了研究,提出一种改进的图分解算法将车身装配结构最优地分解为一组部件.以白车身侧围的装配模型为例,将结构的几何图形转化为与之对应的关系拓扑图,再分割该关系拓扑图为一组工程约束下的单连通不交叉子图集,结合遗传算法中的算子操作,利用有限单元法分析并计算得到产品几何图形的最优分割,采用NSGA-Ⅱ算法并实现该装配体综合性能最优的目标.     

两大部类持续扩大再生产的优化

基于经典的马克思两大部类社会再生产公式,建立了离散确定型的持续扩大再生产的优化问题的动态规划模型.在生产资料部类的不变资本产出率高于另一部类的条件下,动态规划的指标函数是作为决策变量的生产资料部类积累率的单调函数,因而可以使用逆序解法或者顺序解法,获得唯一的最优策略和最优指标函数.借助《资本论》中的一个举例,计算验证了最优解.     

A new approach to pointwise heat kernel upper bounds on doubling metric measure spaces

On doubling metric measure spaces endowed with a strongly local regular Dirichlet form, we show some characterisations of pointwise upper bounds of the heat kernel in terms of global scale-invariant inequalities that correspond respectively to the Nash inequality and to a Gagliardo–Nirenberg type inequality when the volume growth is polynomial. This yields a new proof and a generalisation of the well-known equivalence between classical heat kernel upper bounds and relative Faber–Krahn inequalities or localised Sobolev or Nash inequalities. We are able to treat more general pointwise estimates, where the heat kernel rate of decay is not necessarily governed by the volume growth. A crucial role is played by the finite propagation speed property for the associated wave equation, and our main result holds for an abstract semigroup of operators satisfying the Davies–Gaffney estimates.     

平板折叠桌的设计模型

根据折叠桌的运动特征,选取折叠桌的四分之一为研究对象,建立任意角度下桌脚点的运动变化模型。考虑到产品稳固性、加工便利性和节约用材三方面对加工参数的影响,对折叠桌进行受力分析,得到多目标组合优化模型,用以确定出折叠桌的最优设计参数。针对用户提出的桌面形状要求,建立桌脚曲线的参数方程。作为模型推广,以椭圆状折叠桌为例,运用Matlab画出了桌脚边缘线在折叠过程中的动态变化示意图。同时,又深入研究Robert van Embricqs的滑动折叠桌,建立了新的桌脚曲线参数方程。最后,运用Matlab对多种形状折叠桌进行仿真,编写多目标优化算法,得出了最优加工参数,并进行了算法描述。