Structural topology optimization using a genetic algorithm with a morphological geometric representation scheme

This paper describes a versatile methodology for solving topology design optimization problems using a genetic algorithm (GA). The key to its effectiveness is a geometric representation scheme that works by specifying a skeleton which defines the underlying topology/connectivity of a structural continuum together with segments of material surrounding the skeleton. The required design variables are encoded in a chromosome which is in the form of a directed graph that embodies this underlying topology so that appropriate crossover and mutation operators can be devised to recombine and help preserve any desirable geometry characteristics of the design through succeeding generations in the evolutionary process. The overall methodology is first tested by solving ‘target matching’ problems—simulated topology optimization problems in each of which a ‘target’ geometry is first created and predefined as the optimum solution, and the objective of the optimization problem is to evolve design solutions to converge towards this target shape. The methodology is then applied to design two path-generating compliant mechanisms—large-displacement flexural structures that undergo some desired displacement paths at some point when given a straight line input displacement at some other point—by an actual process of topology/shape optimization.     

Optimum design of nonlinear structures with path dependent reponse

Optimum design of structures with path dependent response is studied in this paper. The direct differentiation and the adjoint structure methods of design sensitivity analysis are summarized. The reference volume concept is used to unify the conventional and shape design problems. It is concluded that the direct differentiation method is more effective for this class of problems. The design sensitivity analysis — developed with continuum formulation — is discretized using the finite element method. Two cases for an example problem are optimized using a sequential quadratic programming algorithm to demonstrate how the developed procedures work and to study the optimization process for the problems with path dependent response.     

Optimal trajectory planning for robots under the consideration of stochastic parameters and disturbances

Efficient control strategies of robots should cause only low on-line correction expenses. Hence, the mostly available statistical and a priori informations about the random parameters and disturbances of the underlying mechanical system and its environment should be considered already for off-line programming of robots. Measuring the violations of the basic mechanical conditions by means of expected penalty costs, a stochastic optimization problem is obtained for the computation of an optimal open-loop control. The stochastic optimization problem can be solved — after discretization — by parameter optimization.     

Simulation aided design of organizational structures in manufacturing systems using structuring strategies

This paper presents a simulation aided approach for designing organizational structures in manufacturing systems. The approach is based on a detailed modeling and characterization of the forecasted order program, especially of elementary processes, activity networks and manufacturing orders. Under the use of the organization modeling system FORM, that has been developed at the ifab-Institute of Human and Industrial Engineering of the University of Karlsruhe, structuring strategies—e.g., a process-oriented strategy—can be applied in order to design organizational structures in manufacturing systems in a flexible and efficient way. Following that, a dynamical analysis of the created manufacturing structures can be carried out with the simulation tool FEMOS, that has also been developed at the ifab-Institute. The evaluation module of FEMOS enables to measure the designed solutions with the help of logistical—e.g., lead time degree—and organizational—e.g., degree of autonomy—key data. This evaluation is the basis for the identification of effective manufacturing systems and also of improvement potentialities. Finally, a case study is presented in this paper designing and analyzing different organizational structures of a manufacturing system where gear boxes and robot grip arms were manufactured.     

A Formal Framework for Web Services Coordination

Recently the term Web Services Choreography has been introduced to address some issues related to Web Services Composition and Coordination. Several proposals for describing Choreography for Business Processes have been presented in the last years and many of these languages (e.g. BPEL4WS) make use of concepts as long-running transactions and compensations for coping with error handling. However, the complexity of BPEL4WS makes it difficult to formally define this framework, thus limiting the formal reasoning about the designed applications. In this paper, we formally address Web Services Coordination with particular attention to Web transactions. We enhance our past work - the Event Calculus - introducing two main novelties: i) a multicast event notification mechanism, and ii) event scope names binding. The former enables an easier specification of complex coordination scenarios — such as E-commerce applications require — while the latter allows many new interesting behaviors which can be very useful in business scenarios: the introduction of private event scope names — used to deal with security and privacy — and a dynamic event scopes definition that can be used to manage multiple instances of the same application.     

Stochastic quasigradient method for optimizing the parameters of dynamic systems

Two-stage stochastic optimization of dynamic system parameters is considered. It is shown that the original optimization problem can be approximated with any degree of accuracy by a finite-dimensional minimax stochastic problem. An Arrow—Hurwicz type stochastic quasigradient algorithm is proposed for solving such problems.Translated from Kibernetika, No. 4, pp. 104–107, 130, July–August, 1990.     

New classes of finite-dimensional nonlinear filters

We derive sufficient conditions for the estimation algebras of two special classes of nonlinear estimation systems to be finite dimensional. By carrying out the Brockett—Wei—Norman program new classes of finite-dimensional filters are obtained. These systems can be regarded respectively as extensions of the Kalman—Bucy filters and the Benes filters.     

工作流系统性能分析与优化方案

随着企业业务流程信息化建设的推进,对核心业务领域的流程化管理已成为实现信息化水平进一步提升的重要基础,工作流系统作为基础设施,其性能在一定程度上决定了业务流程流转的效率.本文通过对工作流系统性能的量化分析,得出其性能指标与数据库规模的量化关系,从而为性能优化工作提出关键因素和技术切入点,在此基础上,本文结合数据库机制对工作流性能优化方案进行了研究和实现,提出了一种有效的算法,实现了归档机制,从而达到提升工作流系统性能优化的最终目的.     

Evaluating solution sets of <Emphasis Type="Italic">a posteriori</Emphasis> solution techniques for bi-criteria combinatorial optimization problems

The quality of an approximate solution for combinatorial optimization problems with a single objective can be evaluated relatively easily. However, this becomes more difficult when there are multiple objectives. One potential approach to solving multiple criteria combinatorial optimization problems when at least one of the single objective problems is NP-complete, is to use an a posteriori method that approximates the efficient frontier. A common difficulty in this type of approach, however, is evaluating the quality of approximate solutions, since sets of multiple solutions should be evaluated and compared. This necessitates the use of a comparison measure that is robust and accurate. Furthermore, a robust measure plays an important role in metaheuristic optimization for tuning various parameters for evolutionary algorithms, simulated annealing, etc., which are frequently employed for multiple criteria combinatorial optimization problems. In this paper, the performance of a new measure, which we call Integrated Convex Preference (ICP) is compared to that of other measures appearing in the literature through numerical experiments—specifically, we use two a posteriori solution techniques based on genetic algorithms for a bi-criteria parallel machine scheduling problem and evaluate their performance (in terms of solution quality) using different measures. Experimental results show that the ICP measure evaluates the solution quality of approximations robustly (i.e., similar to visual comparison results) while other alternative measures can misjudge the solution quality. We note that the ICP measure can be applied to other non-scheduling multiple objective combinatorial optimization problems, as well.     

Optimizing responses to broadcast messages in radio networks

Algorithms to optimize the performance of response traffic for broadcast messages in a packet-switched radio network are studied. The situation considered here involves a source node sending a broadcast message to all destinations and collecting positive response packets from these destinations in a fully connected packet radio network. The exact value of the number of destination nodes is unknown. A contention-based two-level protocol is described. Based on the protocol, an optimization problem is formulated in order to minimize the time for the source node to receive all the responses. Several algorithms are presented and numerical results of the corresponding optimization problems are obtained. These optimization problems are treated by the methods of dynamic programming. An extension of the basic scheme—multicast instead of full broadcast message—is also studied.This work was supported by the US Army Research Office under Contract No. DAAG29-84-K-0084.     

A Variational Maximum Principle for Classical Optimal Control Problems

A necessary condition of optimality—the variational maximum principle—for continuous dynamic optimization problems under linear unbounded control and trajectory terminal constraints is studied. It holds for optimal control problems, which are characterized by the commutativity of vector fields corresponding to the components of a linear control in the dynamic system (Frobenius-type condition). For these problems, the variational maximum principle, being a first-order necessary condition of optimality, is a stronger version of the Pontryagin maximum principle. Examples are given.     

A simple approach for robust economic design of control charts

Robust economic control chart designs incorporating robustness with regard to the uncertainty in the cost and process parameters, reported in the literature, fall into two broad categories. One category of robust economic designs considers the uncertainty in the estimates of the cost and process parameters and makes the design suitable to operate well in any scenario arising out of the uncertainty. Other category of robust economic design considers different possible discrete scenarios for a single process and makes the control chart robust to all possible scenarios. The approach suggested for the robust designs for each category is different and somewhat complicated. The present paper proposes a design approach by introducing a simple statistic for the robust economic design problem of a ‘process with multiple scenarios’. SGA has been used in the optimization. The suggested statistic handles the information regarding the relative frequency of occurrence of each scenario of the process for the robust designs.     

Integrated design and control for robust performance: Application to an MSMPR crystallizer

The interplay of different types of performance constraints in an integrated design and control problem is studied by means of a case study. This integrated problem is based on a recent method for robust process design [M. Mönnigmann, W. Marquardt, Normal vectors on manifolds of critical points for parametric robustness of equilibrium solutions of ODE systems, J. Nonlinear Sci. 12 (2002) 85–112; M. Mönnigmann, W. Marquardt, Steady state process optimization with guaranteed robust stability and feasibility, AIChE J. 49 (12) (2003) 3110–3126; M. Mönnigmann, W. Marquardt, Steady state process optimization with guaranteed robust stability and flexibility: application to HDA reaction section, Ind. Eng. Chem. Res. 44 (2005) 2737–2753; W. Marquardt, M. Mönnigmann, Constructive nonlinear dynamics in process systems engineering, Comput. Chem. Eng. 29 (2005) 1265–1275; M. Mönnigmann, Constructive nonlinear dynamics methods for the design of chemical engineering processes, Ph.D. Thesis, RWTH Aachen University, 2003]. The design is found by means of a steady-state optimization problem accounting for process economics and performance requirements. In particular, the latter are represented by constraints which guarantee a user-specified performance of the design in spite of parametric uncertainties. For the first time, two types of dynamic performance constraints are used simultaneously within the adopted framework. These are constraints on time-domain performance indicators as well as on the asymptotic dynamic process behavior. Furthermore, the effect of uncertainty in both, design and model parameters, is accounted for. A key strength of the suggested framework is the direct quantification of the trade-offs between economics and dynamic performance requirements for a selection of uncertainty scenarios. A series of different integrated design and control problems are formulated and solved for a continuous mixed-suspension mixed-product removal (MSMPR) crystallizer. The process exhibits a complex nonlinear behavior and represents a challenging example. The results of the case study allow an in depth understanding of the interactions of design and control for the underlying process.     

Computer systems simulation in education: Description of an experience

Computer Simulation will play an important role in future changes in Education. Here we will review how the Spanish National Project for Computers in Education, called Atenea, looks at Modelling and Simulation and how the first training courses for teachers, recommended by this project, are being carried out. We will give particular attention to the applications of the Simulation in the classroom using System Dynamics techniques. A real case study, developed by the pupils of a Simulation course for teachers, is outlined showing numerical and graphics results. Afterwards, SDSE—System Dynamics Simulator for Education—is superficially described: it is a microcomputer based system which has been developed by the authors to assist the process of building and simulating System Dynamics models in educative environments.Finally, some pedagogical applications, alternatives of use and major problems of the Simulation in educational environments are presented.     

Smooth curve extraction by mean field annealing

In this paper, we attack the figure — ground discrimination problem from a combinatorial optimization perspective. In general, the solutions proposed in the past solved this problem only partially: either the mathematical model encoding the figure — ground problem was too simple or the optimization methods that were used were not efficient enough or they could not guarantee to find the global minimum of the cost function describing the figure — ground model. The method that we devised and which is described in this paper is tailored around the following contributions. First, we suggest a mathematical model encoding the figure — ground discrimination problem that makes explicit a definition of shape (or figure) based on cocircularity, smoothness, proximity, and contrast. This model consists of building a cost function on the basis of image element interactions. Moreover, this cost function fits the constraints of aninteracting spin system, which in turn is a well suited physical model to solve hard combinatorial optimization problems. Second, we suggest a combinatorial optimization method for solving the figure — ground problem, namely mean field annealing which combines the mean field approximation and annealing. Mean field annealing may well be viewed as a deterministic approximation of stochastic methods such as simulated annealing. We describe in detail the theoretical bases of this method, derive a computational model, and provide a practical algorithm. Finally, some experimental results are shown for both synthetic and real images.This research has been sponsored in part by Commissariat à l'Energie Atomique, and in part by the ORASIS project (PRC Communications Homme/Machine).     

States of a Map Flow of Events: Optimal Estimation by the Maximal a Posteriori State Probability Criterion

The Optimal estimation of the states of a MAP—a particular case of the BMAP—flow of events is studied. Expressions for the a posteriori probabilities of the states of the control process of the MAP flow are derived. An optimal estimation algorithm for determining the states from the maximal a posteriori state probabilities is designed and the numerical results it generated in imitation modelling of an event flow are presented.     

Continuous stochastic logic characterizes bisimulation of continuous-time Markov processes

In a recent paper Baier et al. [Lecture Notes in Computer Science, Springer-Verlag, 2000, p. 358] analyzed a new way of model-checking formulas of a logic for continuous-time processes—called continuous stochastic logic (henceforth CSL)—against continuous-time Markov chains—henceforth CTMCs. One of the important results of that paper was the proof that if two CTMCs were bisimilar then they would satisfy exactly the same formulas of CSL. This raises the converse question—does satisfaction of the same collection of CSL formulas imply bisimilarity? In other words, given two CTMCs which are known to satisfy exactly the same formulas of CSL does it have to be the case that they are bisimilar? We prove that the answer to the question just raised is “yes”. In fact we prove a significant extension, namely that a subset of CSL suffices even for systems where the state space may be a continuum. Along the way we prove a result to the effect that the set of Zeno paths has measure zero provided that the transition rates are bounded.     

An approach to automation of optimizing transformations of algorithms and programs

The paper describes the construction principles of the DIAMANT block — an interactive transformation machine. The functional capabilities of the block are demonstrated in application to formal transformation (optimization) of the shuttle sort algorithm as generated in the MUL'TIPROTSESSIST system.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 127–137, September–October, 1991.     

On box-section arches optimized against buckling

Thin-walled box-section circular arches loaded by a radial pressure are optimized with respect to their stability. Beside the overall both in-plane and out-of-plane buckling local web and flange instability is considered. The optimization aim is to determine either optimal values of cross-section dimensions — parametrical formulation or optimal functions of these dimensions — variational design. For the latter case suitable optimality conditions are derived by use of Pontryagin's maximum principle. The required modality of the problem formulation is discussed and selected numerical results are presented.     

Modelling and optimization of grinding processes

The paper describes different methods for modelling and optimization of grinding processes. First the process and product quality characterizing quantities have to be measured. Afterwards different model types, e.g. physical–empirical basic grinding models as well as empirical process models based on neural networks, fuzzy set theory and standard multiple regression methods, are discussed for an off-line process conceptualization and optimization using a genetic algorithm. The assessment of grinding process results, which build the individuals in the genetic algorithm's population, is carried out using a target tree method. The methods presented are integrated into an existing grinding information system, which is part of a three control loop system for quality assurance.