Solving maximum fuzzy clique problem with neural networks and its applications

The maximum clique problem is an important problem in graph theory. Many real-life problems are still being mapped into this problem for their effective solutions. A natural extension of this problem that has emerged very recently in many real-life networks, is its fuzzification. The problem of finding the maximum fuzzy clique has been formalized on fuzzy graphs and subsequently addressed in this paper. It has been shown here that the problem reduces to an unconstrained quadratic 0–1 programming problem. Using a maximum neural network, along with mutation capability of genetic adaptive systems, the reduced problem has been solved. Empirical studies have been done by applying the method on stock flow graphs to identify the collusion set, which contains a group of traders performing unfair trading among themselves. Additionally, it has been applied on a gene co-expression network to find out significant gene modules and on some benchmark graphs.     

Some duality relationships for the generalized Neyman-Pearson problem

In 1963, Kuhn presented a dual problem to a relatively well-known location problem, variously referred to as the generalized Fermat problem and the Steiner-Weber problem. The purpose of this paper is to point out how Kuhn's results can be adapted to provide a dual to the generalized Neyman-Pearson problem, a problem of fundamental interest in statistics, which has applications in control theory and a number of other areas. The Neyman-Pearson problem, termed the dual problem, is a constrained maximization problem and may be considered to be a calculus-of-variations analog to the bounded-variable problem of linear programming. When the dual problem has equality constraints, the primal problem is an unconstrained minimization problem. Duality results are also obtained for the case where the dual problem has inequality constraints.This work was partially supported by the National Science Foundation, Grant Nos. NSF-GK-1571 and NSF-GK-3038. The authors would like to acknowledge the very useful comments of one of the referees, which led to more direct and general proofs of Properties 2.3 and 2.6.     

三种新变形的全一问题

该文研究三种新变形的全一问题及最小全一问题. 原始的全一问题可被形象的称为顶点点亮顶点问题, 而这三类新问题则分别被称为顶点点亮边问题,边点亮顶点问题,边点亮边问题. 顶点点亮顶点问题已经得到了广泛的研究. 比如,解的存在性问题和求解的有效算法已经被解决,一般图上的最小顶点点亮顶点问题已经被证明是NP- 完备的,树、单圈图和双圈图上的最小顶点点亮顶点问题的线性时间最优算法也已被给出等. 该文对于顶点点亮边问题,证明一个图有解当且仅当它是二部图,因此只可能有两组解和最优解. 对于边点亮顶点问题,证明一个图有解当且仅当它包含偶数个顶点,并通过将其最优问题多项式变换成最小权的完美匹配问题,得出一般图上的最小边点亮顶点问题可在多项式时间内求解. 边点亮边问题可归约成线图上的顶点点亮顶点问题.     

Dirichlet Problem for a Fractional-Order Ordinary Differential Equation with Retarded Argument

A solution of the Dirichlet problem for a fractional-order ordinary differential equation has been found. Green’s function has been constructed for the problem concerned. The problem solution has been written in terms of Green’s function. A theorem on the existence and uniqueness of a solution of the posed problem has been proved, and a condition for its unique solvability has been derived. It is shown that the condition of solvability may only be violated a finite number of times.     

An Algorithm for the 0-1 Equality Knapsack Problem

The 0-1 knapsack problem is a linear integer-programming problem with a single constraint and binary variables. The knapsack problem with an inequality constraint has been widely studied, and several efficient algorithms have been published. We consider the equality-constraint knapsack problem, which has received relatively little attention. We describe a branch-and-bound algorithm for this problem, and present computational experience with up to 10,000 variables. An important feature of this algorithm is a least-lower-bound discipline for candidate problem selection.     

Notes on Duality in Second Order and p -Order Cone Optimization

Recently, the so-called second order cone optimization problem has received much attention, because the problem has many applications and the problem can in theory be solved efficiently by interior-point methods. In this note we treat duality for second order cone optimization problems and in particular whether a nonzero duality gap can be obtained when casting a convex quadratically constrained optimization problem as a second order cone optimization problem. Furthermore, we also discuss the p -order cone optimization problem which is a natural generalization of the second order case. Specifically, we suggest a new self-concordant barrier for the p -order cone optimization problem.     

指派问题在供应商选优决策中的应用

通常供应链中供应商选优问题为多指标决策问题,本将此问题视为指派问题。指派问题中的关键是确定“效率”矩阵,本充分利用供应商单排序结果,评价指标权重以及供应商指标评价值构造了“效率”矩阵,建立了供应商综合选优指派问题模型,案例试算表明该方法合理、有效,为多指标方案决策提供了又一种可行的决策方法。     

On minimizing the duration of transportation

The problem of minimizing the duration of transportation has been studied. The problem has been reduced to a goal programming-type problem which readily lends itself to solution by the standard transportation method. This approach to the solution of the problem is very much different from all other existing ones.     

Perturbation singulière d'un problème de frottement sec non monotone

In this Note we deal with a singularly perturbed system constituted by a differential inclusion which has a unique solution for each value of the perturbation parameter. The associated degenerated problem, that corresponds to a dynamic dry friction problem, has many solutions. We show that perturbed problem solutions converge to a particular solution of the degenerated problem when the perturbation parameter goes to zero. The singular perturbation approach allows an analysis of a criterion used to select a solution of the degenerated problem, and suggests a method to study more elaborated dry friction problems.     

An Exact Solution Method for the MTSP

A new mathematical model for the multi-travelling salesman problem (MTSP) is presented. The MTSP formulation is modified, and a branch-and-bound algorithm for solving this problem exactly is developed. The significance of this procedure is that it does not need to transform the problem into a single travelling salesman problem, which has been the case in the dominant algorithms for solving the above problem. Moreover, computational experience has shown that for a fixed number of cities to be visited, the time required to solve the problem decreases markedly as the number of salesmen increases.     

On the Orlicz Minkowski Problem for Polytopes

Quite recently, an Orlicz Minkowski problem has been posed and the existence part of this problem for even measures has been presented. In this paper, the existence part of the Orlicz Minkowski problem for polytopes is demonstrated. Furthermore, we obtain a solution of the Orlicz Minkowski problem for general (not necessarily even) measures.     

Energy-Optimal Multi-Goal Motion Planning for Planar Robot Manipulators

In this work, the energy-optimal motion planning problem for planar robot manipulators with two revolute joints is studied, in which the end-effector of the robot manipulator is constrained to pass through a set of waypoints, whose sequence is not predefined. This multi-goal motion planning problem has been solved as a mixed-integer optimal control problem in which, given the dynamic model of the robot manipulator, the initial and final configurations of the robot, and a set of waypoints inside the workspace of the manipulator, one has to find the control inputs, the sequence of waypoints with the corresponding passage times, and the resulting trajectory of the robot that minimizes the energy consumption during the motion. The presence of the waypoint constraints makes this optimal control problem particularly difficult to solve. The mixed-integer optimal control problem has been converted into a mixed-integer nonlinear programming problem first making the unknown passage times through the waypoints part of the state, then introducing binary variables to enforce the constraint of passing once through each waypoint, and finally applying a fifth-degree Gauss–Lobatto direct collocation method to tackle the dynamic constraints. High-degree interpolation polynomials allow the number of variables of the problem to be reduced for a given numerical precision. The resulting mixed-integer nonlinear programming problem has been solved using a nonlinear programming-based branch-and-bound algorithm specifically tailored to the problem. The results of the numerical experiments have shown the effectiveness of the approach.     

On the solvability of the tricomi problem for the Lavrent’ev-Bitsadze equation with mixed boundary conditions

We study the existence of a regular (classical) solution of the Tricomi problem for the Lavrent’ev-Bitsadze equation with mixed boundary conditions. We find conditions under which the homogeneous problem has only the zero solution and give an example in which the homogeneous Tricomi problem has a nonzero solution. We also study the solvability of the inhomogeneous Tricomi problem.     

Equivalence of the Generalized Vertical Block Linear Complementarity Problems and Linear Complementarity Problems

In this paper, generalization of a vertical block linear complementarity problem associated with two different types of matrices, one of which is a square matrix and the other is a vertical block matrix, is proposed. The necessary and sufficient conditions for the existence of the solution of the generalized vertical block linear complementarity problem is derived and the relationship between the solution set of the generalized vertical block linear complementarity problem and the linear complementarity problem is established. It is proved that the generalized vertical block linear complementarity problem has the P-property if and only if the vertical block linear complementarity problem has the P-property.     

基于遗传算法的多目标可靠性优化

在元件的体积、重量和造价的共同约束下的多级串并联系统的可靠性优化问题是一个具有多局部极值的、非线性的、同时具有整数和实数变量的混合优化问题.将遗传算法和多目标可靠性分配问题相结合,对可靠性分配问题进行求解,得到较好效果,从而得出结论,遗传算法在求解多目标可靠性优化问题中是一种行之有效的方法.     

Generalized best choice problem based on the information economics approach

We consider the problem of choosing the ‘best choice’ among a certain number of objects that are presented to a decision-maker in sequential order. Such a sequential selection problem is commonly referred to as the ‘best choice problem’, and its optimal stopping rule has been obtained either via the dynamic programming approach or via the Markovian approach. Based on the theory of information economics, we propose in the paper the third approach to a generalized version of the best choice problem that is intuitively more appealing. Various types of the best choice problem, such as (1) the classical secretary problem, (2) no information group interview problem, and (3) full information best choice problem with a random walk process, are shown to be special cases of the generalized best choice problem. The modelling framework of information economics has potential for building theory that ultimately would produce practical stopping rules.     

组合设计的大集

组合设计中的大集问题有着悠久的历史和广泛的应用．由于它的难度，长期进展很慢．近二十多年来，在一些新的方法和手段的推动下，大集研究呈现了很好的态势．本文力图对几类主要组合设计大集的概念和研究进展给予概要介绍，以期引起更多的关注。     

Optimal risk sharing with general deviation measures

An optimal risk sharing problem for agents with utility functionals depending only on the expected value and a deviation measure of an uncertain payoff has been studied. The agents are assumed to have no initial endowments. A set of Pareto-optimal solutions to the problem has been characterized, and a particular solution from the set has been suggested. If an equilibrium exists, the suggested solution coincides with an equilibrium solution. As special cases, the optimal risk sharing problem in the form of expected gain maximization and the problem with a linear mean-deviation utility functional including averse and coherent risk measures have been addressed. In the case of expected gain maximization, the existence of an equilibrium has been shown.     

三维欧氏Steiner最小树的Delaunay四面体网格混合智能算法

Steiner最小树问题是组合优化中经典的NP难题,在许多实际问题中有着广泛的应用,而三维欧氏Steiner最小树问题是对二维欧氏Steiner最小树问题的推广。由于三维欧氏Steiner树问题的求解非常困难,至今为止的相关成果较为少见。本文针对该问题,利用Delaunay四面体网格剖分技术,提出了一种混合型智能求解方法,不仅可以尽量避免拓扑结构陷入局部最优,且对较大规模的问题求解亦有良好的效果。算法在Matlab环境下编程实现,经实例测试,获得了满意的效果。