Hierarchical Optimization-Based Approach for Two-Dimensional Rectangular Layout Design Problems

2009 ◽  
Author(s):  
Kikuo Fujita ◽  
Masayuki Kawamoto
Keyword(s):  
Genetic Algorithms ◽  
Pareto Optimality ◽  
Computational Design ◽  
Layout Design ◽  
System Level ◽  
Hierarchical Optimization ◽  
Two Dimensional ◽  
New Paradigm ◽  
Design Problems ◽  
Design Algorithm

This paper proposes a hierarchical optimization-based approach for two-dimensional rectangular layout design problems. While decomposition-based optimization has been a key approach for the complicated design problems under the trend of multidisciplinary design optimization, it has focused on continuous ones. While various approaches for layout design have been developed, they are based on any evolutionary algorithm for effectively handling its combinatorial nature. This paper aims to bring a new paradigm by combining decomposition-based optimization and evolutionary algorithms toward solving complicated layout design problems. In the approach, the Pareto optimality of subsystem-level layout against the optimality of system-level layout is extracted through two-level hierarchical formulation. Then, a computational design algorithm is developed. It represents the layout topology with sequence-pair and the shape of each subsystem or component with the aspect ratio, and optimizes them with genetic algorithms. The Pareto optimality of sub-levels is handled with multi-objective genetic algorithms, in which a set of Pareto are simultaneously generated. Top-level and sub-level layout problems are coordinated through exchange of preferable ranges of shapes and layout. An implemented approach is applied to an example problem for demonstrating its performance and capability.

A Perspective of Hierarchical Layout Design Optimization for Highly Packaged Equipments

2007 ◽  
Author(s):  
Kikuo Fujita ◽  
Masanori Kuriyama ◽  
Takashi Suyama
Keyword(s):  
Genetic Algorithms ◽  
Design Optimization ◽  
Pareto Optimality ◽  
Computational Design ◽  
Layout Design ◽  
System Level ◽  
Shape Design ◽  
Design Problems ◽  
Design Algorithm

This paper discusses a perspective of hierarchical layout design optimization for highly packaged equipments and demonstrates an implementation of an optimization algorithm with a simplified case study. First, the Pareto optimality of subsystem-level shape design against the optimality of system-level shape design is extracted through two-level hierarchical formulation of layout design problems. Then, a computational design algorithm is developed for a class of two-dimensional layout design problems of rectangles, some of which are the results of similar problems defined in its sub-levels. The algorithm represents the layout topology with sequence-pair and the shape of each module or component with the aspect ratio, and optimizes them with genetic algorithms. The Pareto optimality of sub-levels is handled with the functionality of multi-objective optimization of genetic algorithms, in which a set of Pareto are simultaneously generated. Top-level and sub-level layout problems are coordinated through exchange of preferable ranges of shapes and layout. A case study is explored under the developed algorithm. The promises and limitations of the proposed framework is briefly discussed for defining the future works.

Hierarchical Optimization-Based Approach for Two-Dimensional Rectangular Layout Design Problems

2014 ◽  
Vol 14 (4) ◽  
Author(s):  
Kikuo Fujita ◽  
Shintaro Yamasaki ◽  
Masayuki Kawamoto
Keyword(s):  
Evolutionary Algorithms ◽  
Layout Design ◽  
Hierarchical Optimization ◽  
Two Dimensional ◽  
Layout Problem ◽  
Pareto Optima ◽  
Design Problems ◽  
Design Algorithm ◽  
Effective Manner ◽  
Level Problem

In this study, we propose a hierarchical optimization-based approach for two-dimensional rectangular layout design problems. Decomposition-based optimization has been a key approach for complicated design problems in multidisciplinary design optimization (MDO), but the main focus has been design problems where the design variables are continuous. On the other hand, various approaches have been developed for layout design based on evolutionary algorithms, e.g., simulated annealing (SA) and genetic algorithms (GAs) which can handle its combinatorial nature in an effective manner. In the present study, we aim to introduce a new paradigm by combining decomposition-based optimization and evolutionary algorithms for solving complicated layout design problems. In this approach, the original layout problem is decomposed into the top-level layout problem and a set of sublevel layout problems, where the layouts obtained from the sublevel problems are used as components of the top-level problem. Since the preferable shapes of these components are unclear when the sublevel problems are solved, a set of Pareto optima are provided in the sublevel problems and these solutions are used as candidate components in the top-level problem. A computational design algorithm is developed based on this approach, which represents the layout topology with sequence pair and the shape of each subsystem or component with the aspect ratio, and they are optimized using GAs. The Pareto optimality of the sublevels is handled by multi-objective GAs, and a set of Pareto optima is generated simultaneously. The top-level and sublevel layout problems are coordinated via the exchange of preferable ranges for the shapes and layout. This approach was implemented and applied to an example problem to demonstrate its performance and capability.

The Nesting of Two-Dimensional Shapes Using Genetic Algorithms

1995 ◽  
Vol 209 (2) ◽  
pp. 115-124 ◽  
Author(s):  
H S Ismail ◽  
K K B Hon
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Process ◽  
Search Space ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Optimal Solutions ◽  
Spatial Constraints ◽  
Global Optimal ◽  
Optimum Solution ◽  
Rapid Conversion

The general two-dimensional cutting stock problem is concerned with the optimum layout and arrangement of two-dimensional shapes within the spatial constraints imposed by the cutting stock. The main objective is to maximize the utilization of the cutting stock material. This paper presents some of the results obtained from applying a combination of genetic algorithms and heuristic approaches to the nesting of dissimilar shapes. Genetic algorithms are stochastically based optimization approaches which mimic nature's evolutionary process in finding global optimal solutions in a large search space. The paper discusses the method by which the problem is defined and represented for analysis and introduces a number of new problem-specific genetic algorithm operators that aid in the rapid conversion to an optimum solution.

Optimization of block layout design problems with unequal areas: A comparison of MILP and MINLP optimization methods

2005 ◽  
Vol 30 (1) ◽  
pp. 54-69 ◽  
Author(s):  
Ignacio Castillo ◽  
Joakim Westerlund ◽  
Stefan Emet ◽  
Tapio Westerlund
Keyword(s):  
Optimization Methods ◽  
Layout Design ◽  
Design Problems

Direct Coupling of a Two-Dimensional Fan Model in a Turbofan Engine Performance Simulation

2016 ◽  
Author(s):  
Ioannis Templalexis ◽  
Alexios Alexiou ◽  
Vassilios Pachidis ◽  
Ioannis Roumeliotis ◽  
Nikolaos Aretakis
Keyword(s):  
Three Dimensional ◽  
Engine Performance ◽  
System Level ◽  
Design Parameters ◽  
High Fidelity ◽  
Two Dimensional ◽  
Performance Simulation ◽  
Cfd Models ◽  
Component Design ◽  
Complex Phenomena

Coupling of high fidelity component calculations with overall engine performance simulations (zooming) can provide more accurate physics and geometry based estimates of component performance. Such a simulation strategy offers the ability to study complex phenomena and their effects on engine performance and enables component design changes to be studied at engine system level. Additionally, component interaction effects can be better captured. Overall, this approach can reduce the need for testing and the engine development time and cost. Different coupling methods and tools have been proposed and developed over the years ranging from integrating the results of the high fidelity code through conventional performance component maps to fully-integrated three-dimensional CFD models. The present paper deals with the direct integration of an in-house two-dimensional (through flow) streamline curvature code (SOCRATES) in a commercial engine performance simulation environment (PROOSIS) with the aim to establish the necessary coupling methodology that will allow future advanced studies to be performed (e.g. engine condition diagnosis, design optimization, mission analysis, distorted flow). A notional two-shaft turbofan model typical for light business jets and trainer aircraft is initially created using components with conventional map-defined performance. Next, a derivative model is produced where the fan component is replaced with one that integrates the high fidelity code. For both cases, an operating line is simulated at sea-level static take-off conditions and their performances are compared. Finally, the versatility of the approach is further demonstrated through a parametric study of various fan design parameters for a better thermodynamic matching with the driving turbine at design point operation.

scholarly journals Genetic algorithms in computer aided inductor design

2004 ◽  
Vol 23 (3) ◽  
pp. 68-78
Author(s):  
Jean Fivaz ◽  
Willem A. Cronjé
Keyword(s):  
Genetic Algorithms ◽  
Power Electronics ◽  
Computer Aided Design ◽  
Design Tool ◽  
Design Problems ◽  
Characteristic Data ◽  
Computer Aided ◽  
Aided Design

The goal of this investigation is to determine the advantages of using genetic algorithms in computer-aided design as applied to inductors.  These advantages are exploited in design problems with a number of specifications and constraints, as encountered in power electronics during practical inductor design. The design tool should be able to select components, such as cores and wires, from databases of available components, and evaluate these choices based on the components’ characteristic data read from a database of manufacturers’ data-sheets.  The proposed design must always be practically realizable, as close to the desired specifications as possible and within any specified constraints.

iPattern

2017 ◽  
Vol 6 (2) ◽  
pp. 12-27
Author(s):  
Youmna Bassiouny ◽  
Rimon Elias ◽  
Philipp Paulsen
Keyword(s):  
Design Pattern ◽  
Design Patterns ◽  
Three Dimensional ◽  
Computational Design ◽  
Pattern Design ◽  
Design Problems ◽  
Innovative Design ◽  
Rule Based ◽  
Science And Art ◽  
Design Software

Computational design takes a computer science view of design, applying both the science and art of computational approaches and methodologies to design problems. This article proposes to convert design methodologies studied by designers into rule-based computational design software and help them by providing suggestions for designs to build upon given a set of primitive shapes and geometrical rules. iPattern is a pattern-making software dedicated to designers to generate innovative design patterns that can be used in a decorative manner. They may be applied on wallpapers, carpets, fabric textiles, three-dimensional lanterns, tableware, etc. The purpose is to create a modern pattern design collection that adds a new essence to the place. In order to generate creative design patterns, primitive shapes and geometrical rules are used. The generated design pattern is constructed based on the grid of the Flower of Life of the sacred geometry or similar grids constructed using primitive shapes (rectangles, squares and triangles) combined in the layout of the Flower of Life.

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