CATPAC—An interactive software package for control system design

This report describes a dialogue-oriented software package for computer-aided engineering in control instrumentation. It comprises programmed algorithms for process identification, analysis, simulation, and controller design. For this package a novel architecture was developed to enable a user-friendly interactive application of algorithms. The special structure of the system supports the archiving of computed results, and it facilitates the selection of suitable methods by providing interactive aids.     

Wastewater treatment: New insight provided by interactive multiobjective optimization

In this paper, we describe a new interactive tool developed for wastewater treatment plant design. The tool is aimed at supporting the designer in designing new wastewater treatment plants as well as optimizing the performance of already available plants. The idea is to utilize interactive multiobjective optimization which enables the designer to consider the design with respect to several conflicting evaluation criteria simultaneously. This is more important than ever because the requirements for wastewater treatment plants are getting tighter and tighter from both environmental and economical reasons. By combining a process simulator to simulate wastewater treatment and an interactive multiobjective optimization software to aid the designer during the design process, we obtain a practically useful tool for decision support. The applicability of our tool is illustrated with a case study related to municipal wastewater treatment where three conflicting evaluation criteria are considered.     

配色设计智能优化的非随机种群方法

配色设计优化方法在形成最终方案时经常面临收敛困难,因为设计师对配色方案的评价进入了不稳定状态,难以在细微差异的方案之间做出准确选择.因此优化方法在完成大规模搜索后,最终的收敛阶段一般仍需设计师手工微调完成.这一阶段显著拉低了整个优化过程的效率.面向图库色彩意象再现的需求,针对交互式遗传算法的收敛阶段开发了基于连续插值的...     

核准与收益不确定性条件下的项目投资决策研究

基于实物期权理论和序贯投资决策理论,建立了政府核准和项目现金流双重不确定条件下的项目投资决策模型.针对两种随机变量的非齐次特征,利用Riskoptimizer软件包设计仿真优化算法进行求解.在给定算例的条件下,定量刻画了核准耗时、核准成本、核准通过率等核准不确定性因素和项目收益对项目投资决策的共同影响.     

Component-oriented decomposition for multidisciplinary design optimization in building design

The potential of Multidisciplinary Design Optimization (MDO) is not sufficiently exploited in current building design practice. I argue that this field of engineering requires a special setup of the optimization model that considers the uniqueness of buildings, and allows the designer to interact with the optimization in order to assess qualities of aesthetics, expression, and building function. For this reason, the approach applies a performance optimization based on resource consumption extended by preference criteria. Furthermore, building design-specific components serve for the decomposition and an interactive way of working. The component scheme follows the Industry Foundation Classes (IFC) as a common Building Information Model (BIM) standard in order to allow a seamless integration into an interactive CAD working process in the future. A representative case study dealing with a frame-based hall design serves to illustrate these considerations. An N-Square diagram or Design Structure Matrix (DSM) represents the system of components with the disciplinary dependencies and workflow of the analysis. The application of a Multiobjective Genetic Algorithm (MOGA) leads to demonstrable results.     

The OptdesX design optimization software

This paper describes the OptdesX design optimization software. The software provides a design environment for optimization of engineering problems. The software supports interactive variable and function selection, optimization with continuous and discrete algorithms, design space graphics, tolerance analysis, and control of noise in numerical derivatives, as well as numerous other features. The software is described and illustrated in terms of a small example problem. The software is available on Unix platforms only. Received December 30, 2000     

A program package for simulation of coupled chemical reactions in flow reactors

A program package KINSIMI for an interactive simulation of homogeneous isothermal reactor systems with an arbitrary elementary kinetics has been developed. The simulation of ideal reactors, tanks-in-series, normal axial dispersion reactors and segregated and maximum mixed tanks-in-series and axial dispersion reactors can be performed with the program package. For the ideal reactors and tanks-in-series both step responses and steady states can be computed. For the axial dispersion, segregation and maximum mixedness models the treatment is limited to a steady state stimulation. For the segregation model, empirical batch reactor kinetics can be used in the computation of continuous reactor performance. The corresponding mathematical models and the numerical algorithms are discussed. Two examples of the application of the package are given. The program package can be used for reactor design as well as for educational purposes in illustrating the influence of different reaction mechanisms and flow patterns on the conversion and product distribution.     

Hierarchical structures of optimization packages

Conclusions The expanding operational potential of application packages (interactive and multiprocessing disciplines, application in systems with complex environment, processing of large volumes of data) necessitated a transition from the one-level to a hierarchical package model, in line with the increasing complexity of the package structure.Not all the levels are necessarily present in the design of specific packages. For example, packages executing in the batch mode without multiprocessing and user-initiated dialog do not need the process synchronization level, whereas the top level-the process level-is realized by a single process (in the operating system sense) with the structure described in [1–3]. Packages whose programs always fit into the main memory do not need the data management level, i.e., the cluster is realized by an abstract application module. The application program level is missing in those packages where the application programs are prepared in advance, rather than being generated in run time.The proposed structure is not restricted to optimization packages: it may be used to typify other classes of method-oriented packages. Structure-driven package design ensures that the package has the required properties, makes it possible to implement the software-engineering approach to the design process, avoids gross design errors, and simplifies package adaptation to different environments. Moreover, the hierarchical package structure allows a more technological approach to the development process, as it leads to more effective application of the methods of hierarchical, modular, and structured programming.Translated from Kibernetika, No. 2, pp. 35–39, March–April, 1982.     

Development of CFRP racing motorcycle rims using a heuristic evolutionary algorithm approach

The scope of this paper is the application of evolutionary optimization methods to the development of composite fibre reinforced plastics (CFRP) racing motorcycle rims. The mass and the moment of inertia of a front and a rear CFRP rim are minimized subject to manufacturing, strength, and stiffness constraints. The stacking sequence of the composite laminates is optimized by applying a sophisticated parameterization concept making an excellent compromise between a huge variety of structure properties and a reasonable number of optimization parameters. The mechanical properties are simulated using the finite element analysis package ANSYS . Resulting displacement and Tsai–Wu index values are combined with the mass of the rim in order to assign a fitness value to each different design solution. The smart formulation of the fitness function allows the exploration of solutions close to the required strength and stiffness properties. The proprietary software DynOPS is utilized as an optimization engine. It links an evolutionary algorithm to arbitrary simulation programs and controls the entire optimization process. The sophisticated parameterization concept, together with the fitness function formulation, are the basis for the development of CFRP motorcycle rims decisively lighter than state-of-the-art magnesium alloy rims.     

A general purpose real-world structural design optimization computing platform

Structural optimization has matured from a narrow academic discipline, where researchers focused on optimum design of small idealized structural components and systems, to become the basis in modern design of complex structural systems. Some software applications in recent years have made these tools accessible to professional engineers, decision-makers and students outside the structural optimization research community. These software applications, mainly focused on aerospace, aeronautical, mechanical and naval structural systems, have incorporated the optimization component as an additional feature of the finite element software package. On the other hand though there is not a holistic optimization approach in terms of final design stage for real-world civil engineering structures such as buildings, bridges or more complex civil engineering structures. The optimization computing platform presented in this study is a generic real-world optimum design computing platform for civil structural systems and it is implemented within an innovative computing framework, founded on the current state of the art in topics like metaheuristic optimization, structural analysis and parallel computing. For demonstration purposes the application of the optimization computing platform in five real-world design projects is presented.     

A simulation model of a sulphuric acid production process as an integrated part of an energy system

Power plant process simulation software is well-suited for the modelling of energy systems and more importantly, tools for analysing the energy efficiency are often built into the software. This work presents the development of a simulation model for a sulphuric acid plant using a commercial software package for power plant process simulation. This will be of value to for instance small consultant and engineering companies involved with audits and analysis of energy systems. For small sized companies the cost of acquiring and maintaining many different specialised software packages will be noticeable. However, companies involved with audits and analysis of energy systems will in most cases have access to at least one software package for power plant process calculations. The use of this kind of software for also modelling chemical plants would be valuable to these companies. The results of this work shows that it is possible to use an inexpensive but powerful power plant process simulation software for modelling a common chemical process as a part of a large energy system.     

Software prototype for solving multi-objective machining optimization problems: Application in non-conventional machining processes

For an effective and efficient application of machining processes it is often necessary to consider more than one machining performance characteristics for the selection of optimal machining parameters. This implies the need to formulate and solve multi-objective optimization problems. In recent years, there has been an increasing trend of using meta-heuristic algorithms for solving multi-objective machining optimization problems. Although having the ability to efficiently handle highly non-linear, multi-dimensional and multi-modal optimization problems, meta-heuristic algorithms are plagued by numerous limitations as a consequence of their stochastic nature. To overcome some of these limitations in the machining optimization domain, a software prototype for solving multi-objective machining optimization problems was developed. The core of the developed software prototype is an algorithm based on exhaustive iterative search which guarantees the optimality of a determined solution in a given discrete search space. This approach is justified by a continual increase in computing power and memory size in recent years. To analyze the developed software prototype applicability and performance, four case studies dealing with multi-objective optimization problems of non-conventional machining processes were considered. Case studies are selected to cover different formulations of multi-objective optimization problems: optimization of one objective function while all the other are converted into constraints, optimization of a utility function which combines all objective functions and determination of a set of Pareto optimal solutions. In each case study optimization solutions that had been determined by past researchers using meta-heuristic algorithms were improved by using the developed software prototype.     

Coupling dynamic simulation and interactive multiobjective optimization for complex problems: An APROS-NIMBUS case study

Dynamic process simulators for plant-wide process simulation and multiobjective optimization tools can be used by industries as a means to cut costs and enhance profitability. Specifically, dynamic process simulators are useful in the process plant design phase, as they provide several benefits such as savings in time and costs. On the other hand, multiobjective optimization tools are useful in obtaining the best possible process designs when multiple conflicting objectives are to be optimized simultaneously. Here we concentrate on interactive multiobjective optimization. When multiobjective optimization methods are used in process design, they need an access to dynamic process simulators, hence it is desirable for them to coexist on the same software platform. However, such a co-existence is not common. Hence, users need to couple multiobjective optimization software and simulators, which may not be trivial. In this paper, we consider APROS, a dynamic process simulator and couple it with IND-NIMBUS, an interactive multiobjective optimization software. Specifically, we: (a) study the coupling of interactive multiobjective optimization with a dynamic process simulator; (b) bring out the importance of utilizing interactive multiobjective optimization; (c) propose an augmented interactive multiobjective optimization algorithm; and (d) apply an APROS-NIMBUS coupling for solving a dynamic optimization problem in a two-stage separation process.     

FOPS: A new framework for the optimization with variable number of dimensions

A single‐ and multi‐objective optimization package is presented and described in detail. It contains an ensemble of local and global optimization routines. Procedures controlling variable number of dimensions are implemented as well, which is a rare feature among optimization oriented packages. The package is provided as a MATLAB toolbox. It excels in versatility and extensibility, which is demonstrated on a series of examples covering classical electromagnetism and antenna design. It is taken for granted that defining parameters of the optimization method can be set prior to the simulation run. However, its effective performance can be changed during the optimization run thanks to the full control feature. Moreover, it opens new possibilities in merging various algorithms into hybrids, performing complex dynamic programming tasks, or exploiting third party software. These advantages render the package as a perfect tool to deal with nowadays challenging engineering tasks.     

Formulating efficient software solution for digital image processing system

Digital image processing systems are complex, being usually composed of different computer vision libraries. Algorithm implementations cannot be directly used in conjunction with algorithms developed using other computer vision libraries. This paper formulates a software solution by proposing a processor with the capability of handling different types of image processing algorithms, which allow the end users to install new image processing algorithms from any library. This approach has other functionalities like capability to process one or more images, manage multiple processing jobs simultaneously and maintain the manner in which an image was processed for later use. It is a computational efficient and promising technique to handle variety of image processing algorithms. To promote the reusability and adaptation of the package for new types of analysis, a feature of sustainability is established. The framework is integrated and tested on a medical imaging application, and the software is made freely available for the reader. Future work involves introducing the capability to connect to another instance of processing service with better performance. Copyright © 2015 John Wiley & Sons, Ltd.     

基于多近似模型的交互式遗传算法

人的疲劳向题是交互式遗传算法的核心问题,它制约了交互式遗传算法在复杂优化问题中的应用.为了解决该问题,本文提出基于多近似模型的交互式遗传算法.该算法首先将搜索空间划分,然后利用传统交互式遗传算法得到的数据,在不同子空间生成不同的近似模型,最后采用该模型近似人对进化个体的评价,从而减少人评价的数量,有效解决人的疲劳问题.算法性能分析及在服装进化设计系统中的应用验证了其有效性.     

DISPRO: A discrete programming package

Conclusions The DISPRO package is open for modification and further development. Its modular structure allows expansion of the source language, incorporation of new system and application modules, realization in the current version of an interface with DBMS and other application packages (e.g., report generator, matrix generator), synthesis of the package with PL/1 and FORTRAN IV programming systems.The first version of DISPRO released in 1980 has successfully passed the requisite acceptance tests and is now officially part of the optimization packages supported by ES series computers. As outlined in this article, the package has tremendous possibilities for solving a wide range of discrete optimization problems. So far, certain classes of discrete programming problems could be solved by LP ASU [31], VEKTOR-1, the Z-system [58], and TsP [31] application packages. In addition, some packages have been developed in recent years for mathematical programming and operations research (DISPLAN, an interactive planning system [60]; PTP, optimization of transportation problems [58]; PMP, separable and parametric linear programming; DILOS, interactive system for unconstrained optimization, nonlinear programming, and optimal control; ORBITAL', unconstrained optimization and approximation [61]; NDO, nondifferentiable and stochastic optimization [62]; and other less known packages reviewed, in particular, in [58].New optimization packages are currently being developed in response to increased demands for quality, efficiency, and applicability in various MIS and ADPS. The next version of the DISPRO package is being designed on the basis of the appropriate principles and requirements for modern method-oriented packages, including accumulation and analysis of package performance data (these data may be used to improve the package software and structure), large dimensionality of the relevant problems, operating reliability, commercial development of packages, and their usability in integrated data processing systems.In conclusion, DISPRO was developed by the concerted effort of a large team. In particular, we should mention the contributions of Yu. M. Ermol'ev, V. L. Volkovich, A. I. Kuksa, Yu. Yu. Chervak, N. S. Podgorodetskaya, E. S. Karpinka, V. M. Sementsova, V. I. Artemenko, and other members of the team.Translated from Kibernetika, No. 3, pp. 117–137, May–June, 1981.     

智能优化在软件测试中的应用综述

软件测试是软件开发活动中一个关键且耗时的环节,其核心是生成满足特定准则的测试数据.随着软件复杂程度的不断增加,软件测试的难度也越来越高.使用遗传算法等智能优化方法解决复杂软件的测试问题,是近年来软件工程领域的一个研究热点.鉴于此,针对智能优化在软件测试的应用进行综述,首先介绍软件测试的基本原理和方法;然后介绍智能优化在...     

基于HYSYS的催化重整流程模拟及其应用

选取催化重整18集总31反应集总动力学模型,以流程模拟软件HYSYS为工具,建立了催化重整过程稳态模型。将模型参数估计问题转化为优化问题,在MATLAB中使用ActiveX技术调用HYSYS模型,利用Marquardt算法对模型进行参数估计,并利用工业数据对模型进行了验证。基于HYSYS稳态模型对催化重整过程进行了灵敏度分析,得出操作参数、进料性质和产品指标之间的关系,仿真结果与理论分析一致,从而能够对催化重整过程的监控和优化提供指导。