满足重构概率约束的更少贝努利观测

在压缩感知(Compressed sensing, CS)中,一些方法统计地提供了给定观测数量下的信号重构概率. 然而,在重构概率有约束的情况下,现有方法不能找到满足约束的观测. 本文以压缩感知中常用的贝努利观测集为研究对象, 基于贝努利观测的特征和序列压缩感知理论获得了满足重构概率约束的观测. 另外,由于所提方法能从获取的过多观测中移除部分冗余观测, 观测结果包含更少的观测数据. 所提方法有三个优点:满足重构概率约束、 包含更少的观测数据以及具有全局收敛的属性. 理论分析和实验结果验证了所提方法的有效性.     

A parameter free Continuous Ant Colony Optimization Algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach

This paper describes the application of the newly introduced Continuous Ant Colony Optimization Algorithm (CACOA) to optimal design of sewer networks. Two alternative approaches to implement the algorithm is presented and applied to a storm sewer network in which the nodal elevations of the network are considered as the decision variables of the optimization problem. In the first and unconstrained approach, a Gaussian probability density function is used to represent the pheromone concentration over the allowable range of each decision variable. The pheromone concentration function is used by each ant to randomly sample the nodal elevations of the trial networks. This method, however, will lead to solutions which may be infeasible regarding some or all of the constraints of the problem and in particular the minimum slope constraint. In the second and constrained approach, known value of the elevation at downstream node of a pipe is used to define new bounds on the elevation of the upstream node satisfying the explicit constraints on the pipe slopes. Two alternative formulations of the constrained algorithm are used to solve a test example and the results are presented and compared with those of unconstrained approach. The methods are shown to be very effective in locating the optimal solution and efficient in terms of the convergence characteristics of the resulting algorithms. The proposed algorithms are also found to be relatively insensitive to the initial colony and size of the colony used compared to the original algorithm.     

快速的布料碰撞检测和有效的接触摩擦算法

为了快速处理布料的碰撞检测并获得真实的接触摩擦仿真效果,提出一种基于罚函数的碰撞/接触解决方案.首先,采用质点-弹簧模型进行布料的仿真模拟,在弹簧形变方向添加改进的阻尼力,以减少粒子之间的振荡来保证系统稳定性;其次,采用代数非穿透滤波器对连续碰撞检测算法进行简化求解,快速判断是否存在方程根,提高布料每帧运行的仿真效率;最后,采用库仑约束和接触约束对每个碰撞/接触对进行约束,并结合改进的罚函数法有效地响应所有的碰撞/接触对.实验结果表明,该算法在CPU仿真环境下能快速有效地处理布料的碰撞和接触摩擦,模拟出布料复杂的物理行为,适用于实时的交互应用.     

新型线性先行GA算法在油品调和中的应用

油品调和是生产成品油的关键环节,调和配方决定了利润的最终大小。配方优化模型中物料平衡约束、产品产量约束属于线性约束,但质量指标约束中存在的非线性约束,使整个求解问题成为非线性约束求解问题。针对炼油厂油品调和复杂非线性约束配方优化问题,提出了一种新的线性先行GA算法。通过将线性约束与非线性约束拆分开,先求解凸多面体的全部顶点和极方向,解出满足线性约束的所有可行解所在的可行区域,进而用GA算法在此可行域内,通过优化凸组合的系数,从而达到搜索整个线性解区间的目的,完成非线性优化模型的求解。仿真结果表明,新算法大大缩小了GA算法的搜索空间和需要处理的约束,能快速的获得理想的调和配方,使利润最大并保证对质量卡边的要求。     

Achieving MILP feasibility quickly using general disjunctions

Branch and bound algorithms for Mixed-Integer Linear Programming (MILP) almost universally branch on a single variable to create disjunctions. General linear expressions involving multiple variables are another option for branching disjunctions, but are not used for two main reasons: (i) descendent LPs tend to solve more slowly because of the added constraints, so the overall solution time is increased, and (ii) it is difficult to quickly find an effective general disjunction. We study the use of general disjunctions to reach the first MILP-feasible solution quickly, showing for the first time that general disjunctions can provide speed improvements for hard MILP models. The speed-up is due to new and efficient ways to (i) trigger the inclusion of a general disjunction only when it is likely to be beneficial, and (ii) construct effective general disjunctions very quickly. Our empirical results show performance improvements versus a state of the art commercial MILP solver.     

Relatively quantified constraint satisfaction

The constraint satisfaction problem (CSP) is a convenient framework for modelling search problems; the CSP involves deciding, given a set of constraints on variables, whether or not there is an assignment to the variables satisfying all of the constraints. This paper is concerned with the more general framework of quantified constraint satisfaction, in which variables can be quantified both universally and existentially. We study the relatively quantified constraint satisfaction problem (RQCSP), in which the values for each individual variable can be arbitrarily restricted. We give a complete complexity classification of the cases of the RQCSP where the types of constraints that may appear are specified by a constraint language.     

一种欠约束草图求解方法的研究

基于约束的参数化描述及求解是计算机辅助设计研究的一个热点，欠约束图的求解是参数化设计的基本问题，为了提高欠约束草图求解的参数化设计效率，提出了一种基于隐式约束优先级的欠约束草图求解方法，并首先给出了欠约束图求解的一般方法以及欠约束图的基本特征，提出了利用隐式约束去匹配缺少的显式约束；然后将隐式约束按照一定的规则分成不同的优先级，再利用优先级高的隐式约束去匹配变动约束图中的欠约束，直到完成约束图的有向化；最后，探讨了无尺寸约束图有向化过程中的基本特点，并给出了无尺寸约束图的求解算法和应用实例。实例应用结果表明，效果较好。     

Assessment of system reliability for a stochastic-flow distribution network with the spoilage property

In supply chain management, satisfying customer demand is the most concerned for the manager. However, the goods may rot or be spoilt during delivery owing to natural disasters, inclement weather, traffic accidents, collisions, and so on, such that the intact goods may not meet market demand. This paper concentrates on a stochastic-flow distribution network (SFDN), in which a node denotes a supplier, a transfer station, or a market, while a route denotes a carrier providing the delivery service for a pair of nodes. The available capacity of the carrier is stochastic because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the system reliability, the probability that the SFDN can satisfy the market demand with the spoilage rate under the budget constraint from multiple suppliers to the customer. An algorithm is developed in terms of minimal paths to evaluate the system reliability along with a numerical example to illustrate the solution procedure. A practical case of fruit distribution is presented accordingly to emphasise the management implication of the system reliability.     

Static output feedback control of networked control systems with packet dropout

This article deals with the problem of mean square stability of discrete-time networked control systems (NCSs) over a communication channel subject to packet dropout. By introducing a parameter-independent slack variable with lower triangular structure, the existence of a static output feedback controller is formulated in the form of linear matrix inequalities. Neither equality constraint nor iterative algorithm is involved through the derivation of the controller. Furthermore, a new algorithm is proposed to obtain the admissible packet dropout probability bound for the given controller gain. This is particularly important in the co-design of controller and scheduling for NCSs. The simplicity of the methods is demonstrated by numerical examples.     

Modular design of a hybrid genetic algorithm for a flexible job–shop scheduling problem

The aim of the job–shop scheduling problem is to optimize the task planning in an industrial plant satisfying time and technological constraints. The existing algorithmic and mathematical methods for solving this problem usually have high computational complexities making them intractable. Flexible job–shop scheduling becomes even more complex, since it allows one to assign each operation to a resource from a set of suitable ones. Alternative heuristic methods are only able to satisfy part of the constraints applicable to the problem. Moreover, these solutions usually offer little flexibility to adapt them to new requirements. This paper describes research within heuristic methods that combines genetic algorithms with repair heuristics. Firstly, it uses a genetic algorithm to provide a non-optimal solution for the problem, which does not satisfy all its constraints. Then, it applies repair heuristics to refine this solution. There are different types of heuristics, which correspond to the different types of constraints. A heuristic is intended to evaluate and slightly modify a solution that violates a constraint in a way that avoids or mitigates such violation. This approach improves the adaptability of the solution to a problem, as some changes can be addressed just modifying the considered chromosome or heuristics. The proposed solution has been tested in order to analyse its level of constraint satisfaction and its makespan, which are two of the main parameters considered in these types of problems. The paper discusses this experimentation showing the improvements over existing methods.     

Backtracking and random constraint satisfaction

The average running time used by backtracking on random constraint satisfaction problems is studied. This time is polynomial when the ratio of constraints to variables is large, and it is exponential when the ratio is small. When the number of variables goes to infinity, whether the average time is exponential or polynomial depends on the number of variables per constraint, the number of values per variable, and the probability that a random setting of variables satisfies a constraint. A method for computing the curve that separates polynomial from exponential time and several methods for approximating the curve are given. The version of backtracking studied finds all solutions to a problem, so the running time is exponential when the number of solutions per problem is exponential. For small values of the probability, the curve that separates exponential and polynomial average running time coincides with the curve that separates an exponential average number of solutions from a polynomial number. For larger probabilities the two curves diverge. Random problems similar to those that arise in understanding line drawings with shadows require a time that is mildly exponential when they are solved by simple backtracking. Slightly more sophisticated algorithms (such as constraint propagation combined with backtracking) should be able to solve these rapidly. This revised version was published online in June 2006 with corrections to the Cover Date.     

基于MPLS流量工程的多路径负载均衡方法

对多协议标签交换（MPLS）流量工程负载均衡问题，提出了两种多路径基于约束的负载均衡方法，在LSP建立初期就融入负载均衡思想。在通常的CSPF算法中，对于一个大带宽约束很可能无法找到可行路径，文中所提方法在没有单一路径满足带宽约束时，能将带宽约束划分为两个或多个子约束，并为每一子约束找到约束路径。实验结果表明，所提方法能增加路径建立的成功率，提高网络资源利用率，达到流量均衡。     

Integrating Standard Dependency Schemes in QCSP Solvers

Quantified constraint satisfaction problems (QCSPs) are an extension to constraint satisfaction problems (CSPs) with both universal quantifiers and existential quantifiers.In this paper we apply variab...     

Integrating local and global topological structures for semi-supervised dimensionality reduction

Dimensionality reduction plays an important role in many machine learning tasks. This paper studies semi-supervised dimensionality reduction using pairwise constraints. In this setting, domain knowledge is given in the form of pairwise constraint, which specifies whether a pair of instances belongs to the same class (must-link constraint) or different classes (cannot-link constraint). In this paper, a novel semi-supervised dimensionality reduction method called LGS3DR is proposed, which can integrate both local and global topological structures of the data as well as pairwise constraints. The LGS3DR method is effective and has a closed form solution. Experiments on data visualization and face recognition show that LGS3DR is superior to many existing dimensionality reduction methods.     

Branch-and-bound and PSO algorithms for no-wait job shop scheduling

This paper deals with the no-wait job shop scheduling problem resolution. The problem is to find a schedule to minimize the makespan (\(C_{max}\)), that is, the total completeness time of all jobs. The no-wait constraint occurs when two consecutive operations in a job must be processed without any waiting time either on or between machines. For this, we have proposed two different resolution methods, the first is an exact method based on the branch-and-bound algorithm, in which we have defined a new technique of branching. The second is a particular swarm optimization (PSO) algorithm, extended from the discrete version of PSO. In the proposed algorithm, we have defined the particle and the velocity structures, and an efficient approach is developed to move a particle to the new position. Moreover, we have adapted the timetabling procedure to find a good solution while respecting the no-wait constraint. Using the PSO method, we have reached good results compared to those in the literature.     

Generalized terminal state constraint for model predictive control

A terminal state equality constraint for Model Predictive Control (MPC) laws is investigated, where the terminal state/input pair is not fixed a priori but it is a free variable in the optimization. The approach, named “generalized” terminal state constraint, can be used for both tracking MPC (i.e. when the objective is to track a given steady state) and economic MPC (i.e. when the objective is to minimize a cost function which does not necessarily attains its minimum at a steady state). It is shown that the proposed technique provides, in general, a larger feasibility set with respect to the existing approaches, given the same prediction horizon. Moreover, a new receding horizon strategy is introduced, exploiting the generalized terminal state constraint. Under mild assumptions, the new strategy is guaranteed to converge in finite time, with arbitrarily good accuracy, to an MPC law with an optimally-chosen terminal state constraint, while still enjoying a larger feasibility set. The features of the new technique are illustrated by an inverted pendulum example in both the tracking and the economic contexts.     

具有总能耗约束的柔性作业车间调度问题研究

针对具有总能耗约束的柔性作业车间调度问题（Flexible job shop scheduling problem,FJSP）,提出一种基于帝国竞争算法（Imperialist competitive algorithm,ICA）和变邻域搜索（Variable neighborhood search,VNS）的双阶段算法,该算法在总能耗不超过给定阈值的条件下最小化Makespan和总延迟时间.由于能耗约束不是总能满足且阈值往往难以事先给定,为此,第一阶段,首先,将原问题转化为具有Makespan、总延迟时间和总能耗的三目标FJSP,然后,利用初始帝国构建和帝国竞争的新策略设计一种ICA对问题求解,并根据ICA的结果确定总能耗阈值;第二阶段,应用解的比较新策略、非劣解集更新方法和当前解周期性更新,构建VNS对原问题求解.计算实验和结果分析表明,两阶段算法对于所研究的问题搜索能力强.     

Natural coordinates for the computer analysis of multibody systems

In this paper we will describe a new method for the computer kinematic and dynamic analysis of a wide range of three-dimensional mechanisms or multibody systems. This method is based on a new system of non-independent coordinates that use Cartesian coordinates of points and Cartesian components of unitary vectors in order to describe the position and the motion of the system. Angular coordinates are not used. The kinematic constraint equation comes in two ways, from the rigid-body condition for each element and from the joints or kinematic pairs. The consideration of unitary vectors facilitates considerably the formulation of pair constraints when the pair is associated with a particular direction, as is the case with revolute (R), cylindrical (C), or prismatic (P) pairs. The constraint equations are quadratic in the problem coordinates and they never involve transcendental functions. The dynamic differential equations are obtained in a very simple and effective way from the theorem of virtual power. Finally, two examples will be presented.     

Reliability evaluation of a multistate network subject to time constraint under routing policy

A multistate network is a stochastic network composed of multistate arcs in which each arc has several possible capacities and may fail due to failure, maintenance, etc. The quality of a multistate network depends on how to meet the customer's requirements and how to provide the service in time. The system reliability, the probability that a given amount of data can be transmitted through a pair of minimal paths (MPs) simultaneously under the time constraint, is a proper index to evaluate the quality of a multistate network. An efficient solution procedure is first proposed to calculate it. In order to further enhance the system reliability, the network administrator decides the routing policy in advance to indicate the first and the second priority pairs of MPs. The second priority pair of MPs takes charge of the transmission duty if the first fails. The system reliability under the routing policy can be subsequently evaluated.     

Motion on submanifolds of noninvariant holonomic constraints for a kinematic control system evolving on a matrix Lie group

For a control system on a matrix Lie group with one or more configuration constraints that are not left/right invariant, finding the combinations of (kinematic) control inputs satisfying the motion constraints is not a trivial problem. Two methods, one coordinate-dependent and the other coordinate-free are suggested. The first is based on the Wei–Norman formula; the second on the calculation of the annihilator of the coadjoint action of the constraint one-form at each point of the group manifold. The results are applied to a control system on SE(3) with a holonomic inertial constraint involving the noncommutative part in a nontrivial way. The difference in terms of compactness of the result between the two methods is considerable.