Optimizing creatively in multi-objective optimization
Optimizing creatively in multi-objective optimization
复制标题
多目标优化中的创造性优化
DOI：
10.11575/prism/27214
复制
发表时间：
2015
影响因子：
2.4
通讯作者：
Branko Kolarevic
中科院分区：
文献类型：
--
作者：
Yassin Ashour;Branko Kolarevic
设计师将始终面临设计性能良好的建筑物的挑战，这些建筑物通常是相互冲突和相互竞争的目标。早期设计决策对建筑物的最终性能影响很大，设计师通常无法根据项目的执行标准探索大量的设计方案。这项研究概述了一个“创造性的优化工作流程”，使用多目标优化（MOO）引擎称为章鱼，运行在Grasshopper 3D，参数化建模工具和模拟软件DIVA的日光因素分析。该工作流程利用“创造性的优化工具”，它允许设计人员探索，排序和过滤解决方案，并定量和定性分析所得到的设计解决方案空间的权衡。它使设计师能够在图库中直观地比较替代解决方案，并随后通过基于雷达的图表，平行坐标绘图图和条件域搜索来分析权衡。该反馈工具允许设计者快速有效地识别用于设计开发的潜在解决方案或选择用于进一步优化的优选解决方案，即“创造性地优化”。一个回顾性的设计案例研究，“德鹿特丹'建设，是用来演示的工具的应用。该工作流程展示了减少设计延迟并允许更好地理解设计解决方案的能力。需要进行更多的研究，以更好地了解MOO在设计早期阶段的应用;并进一步改进创造性的优化工具，以适应设计师对更动态和协同过程的需求。
Designers will always face the challenge of designing well-performing buildings using what are often conflicting and competing objectives. Early stage design decisions influence significantly the final performance of a building and designers are often unable to explore large numbers of design alternatives with respect to the performative criteria set for the project. This research outlines a "creative optimization workflow' using a Multi-Objective Optimization (MOO) engine called Octopus that runs within Grasshopper3D, a parametric modeling tool, and simulation software DIVA for daylight factor analysis. The workflow utilizes a "creative optimization tool' which allows the designer to explore, sort and filter solutions, and analyze both quantitatively and qualitatively the trade-offs of the resultant design solution space. It enables the designer to visually compare alternative solutions in a gallery and subsequently analyze trade-offs through a radar-based chart, parallel coordinate plot graphs and conditional domain searches. This feedback tools allows the designer to quickly and efficiently identify potential solutions for either design development or to select preferred solutions for further optimization, i.e. "optimizing creatively'. A retrospective design case study, the "De Rotterdam' building, is used to demonstrate the application of the tools. The workflow demonstrates the ability to reduce design latency and to allow for better understanding of design solutions. Additional research is needed to better understand the application of MOO in the early stages of design; and the further improvement of the creative optimization tools to accommodate the designer's need for a more dynamic and synergistic process.