Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

Planning the GMAW process by constraint propagation

Although the gas metal arc welding (GMAW) process is widely used for joining metals, its planning is still a cumbersome task. The planning procedure involves many complex interrelationships among the process variables and depends heavily on empirical knowledge. Therefore, a solution method that allows a convenient way to represent the domain knowledge and evaluate the process variable relationships is needed. Further, the lack of a strong domain theory to quantify these interrelationships is a deficiency in the planning of the GMAW process. This paper presents a solution method that overcomes this deficiency and introduces a convenient knowledge representation scheme. The solution method considers the planning procedure to be a constraint satisfaction problem (CSP). The AC-4 algorithm is used to obtain arc consistency among nodes in the constraint network and the PC-4 algorithm is applied to obtain path consistency in the network. A modified version of the AC-4 algorithm is developed to reduce the search space and correspondingly reduce the computation time. An example is presented to demonstrate the capability of the method and its potential to reduce lead time.     

On finding optimal and near-optimal lineal spanning trees

The search for good lineal, or depth-first, spanning trees is an important aspect in the implementation of a wide assortment of graph algorithms. We consider the complexity of findingoptimal lineal spanning trees under various notions of optimality. In particular, we show that several natural problems, such as constructing a shortest or a tallest lineal tree, are NP-hard. We also address the issue of polynomial-time, near-optimization strategies for these difficult problems, showing that efficient absolute approximation algorithms cannot exist unlessP = NP.This author's research was supported in part by the Sandia University Research Program and by the National Science Foundation under Grant M IP-8603879.This author's research was supported in part by the National Science Foundation under Grants ECS-8403859 and MIP-8603879.     

以技术进步促进蒸汽能源的节约

本文运用“软科学”一即通过建立数学模型，进行系统分析和系统优化，阐述对蒸汽管网优化运行的方法及原理，达到提高供热效率及节能降耗的目的．     

Branching and pruning: An optimal temporal POCL planner based on constraint programming

A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planners provide an alternative branching scheme but lacking comparable pruning mechanisms do not perform as well. In this paper, a domain-independent formulation of temporal planning based on Constraint Programming is introduced that successfully combines a POCL branching scheme with powerful and sound pruning rules. The key novelty in the formulation is the ability to reason about supports, precedences, and causal links involving actions that are not in the plan. Experiments over a wide range of benchmarks show that the resulting optimal temporal planner is much faster than current ones and is competitive with the best parallel planners in the special case in which actions have all the same duration.¹     

变形镜交连值的优化分析

关于优化光波控制,自适应光学校正是至关重要的一个环节,可用于改善激光光束质量及校正光束在传输过程中气流引起的波前畸变等。变形镜是其核心器件,而交连值是影响变形镜校正精度的关键因素。针对变形镜实际使用时需要对致动器进行一定的约束,利用带约束的最小二乘法,分析了在一定约束条件下交连值变化对变形镜校正精度及控制稳定性的影响。以Zernike像差和以大气湍流模型构造的像差为校正对象,寻找校正效果最好的交连值。结果表明各阶Zernike像差对应的最优交连值差异较大,最优交连值主要分布在15%～35%之间。从控制误差引起的校正效果变化的方面考虑,对正方形致动器排布的最优交连值位于15%～25%区域。     

注射充模过程的压力求解方法及其比较

提出了一个LU局部分解方法来求解注射充模过程的压力方程,并与其他迭代方法进行了比较。LU局部分解法是当矩阵在逐渐变大时,保留已经分解的部分,只对新增加的部分进行分解,因此相当于只对最后的稀疏矩阵进行了分解。计算表明,LU局部分解法比预条件共轭梯度法快大约1个量级,而预条件共轭梯度方法又比超松弛迭代法快大约1个量级。     

Steady-state target optimization designs for integrating real-time optimization and model predictive control

In industrial practice, the optimal steady-state operation of continuous-time processes is typically addressed by a control hierarchy involving various layers. Therein, the real-time optimization (RTO) layer computes the optimal operating point based on a nonlinear steady-state model of the plant. The optimal point is implemented by means of the model predictive control (MPC) layer, which typically uses a linear dynamical model of the plant. The MPC layer usually includes two stages: a steady-state target optimization (SSTO) followed by the MPC dynamic regulator. In this work, we consider the integration of RTO with MPC in the presence of plant-model mismatch and constraints, by focusing on the design of the SSTO problem. Three different quadratic program (QP) designs are considered: (i) the standard design that finds steady-state targets that are as close as possible to the RTO setpoints; (ii) a novel optimizing control design that tracks the active constraints and the optimal inputs for the remaining degrees of freedom; and (iii) an improved QP approximation design were the SSTO problem approximates the RTO problem. The main advantage of the strategies (ii) and (iii) is in the improved optimality of the stationary operating points reached by the SSTO-MPC control system. The performance of the different SSTO designs is illustrated in simulation for several case studies.     

Mapping streaming applications on multiprocessors with time-division-multiplexed network-on-chip

This paper addresses mapping of streaming applications (such as MPEG) on multiprocessor platforms with time-division-multiplexed network-on-chip. In particular, we solve processor selection, path selection and router configuration problems. Given the complexity of these problems, state of the art approaches in this area largely rely on greedy heuristics, which do not guarantee optimality. Our approach is based on a constraint programming formulation that merges a number of steps, usually tackled in sequence in classic approaches. Thus, our method has the potential of finding optimal solutions with respect to resource usage under throughput constraints. The experimental evaluation presented in here shows that our approach is capable of exploring a range of solutions while giving the designer the opportunity to emphasize the importance of various design metrics.     

具有时空约束的TRBAC模型在OA中的应用

本文提出了一个基于TRBAC（Task—Kole Based Access Contr01）具有时空约束的工作流授权模型TSC—TRBAC（Temporarily-SpatiallyConstrained Task—RoleBased Access Contr01）。所谓时空约束即用户执行任务的时候,不仅受到时间约束,而且还受到空间限制,包括对物理空间和逻辑空间的限制,这使得工作流的安全性得以保证。通过将该模型应用到具体的系统中,表明了该模型的可行性。