Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm-Reference-Cited by-同舟云学术

Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm

Published:2016-03-02 Issue:4 Volume:138 Page:
ISSN:1050-0472
Container-title:Journal of Mechanical Design
language:en
Short-container-title:

Author:

McComb Christopher¹,Cagan Jonathan²,Kotovsky Kenneth³

Affiliation:

1. Mem. ASME Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 e-mail:

2. Fellow ASME Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 e-mail:

3. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213 e-mail:

Abstract

Insights uncovered by research in design cognition are often utilized to develop methods used by human designers; in this work, such insights are used to inform and improve computational methodologies. This paper introduces the heterogeneous simulated annealing team (HSAT) algorithm, a multiagent simulated annealing (MSA) algorithm. HSAT is based on a validated computational model of human-based engineering design and retains characteristics of the model that structure interaction between team members and allow for heterogeneous search strategies to be employed within a team. The performance of this new algorithm is compared to several other simulated annealing (SA) based algorithms on three carefully selected benchmarking functions. The HSAT algorithm provides terminal solutions that are better on average than other algorithms explored in this work.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

Link

http://asmedigitalcollection.asme.org/mechanicaldesign/article-pdf/doi/10.1115/1.4032810/6228033/md_138_04_044501.pdf

Reference21 articles.

1. Empirical Studies of Designer Thinking: Past, Present, and Future;ASME J. Mech. Des.,2014

2. Concurrent Optimization of Computationally Learned Stylistic Form and Functional Goals;ASME J. Mech. Des.,2012

3. Cognitive, Collaborative, Conceptual and Creative—Four Characteristics of the Next Generation of Knowledge-Based CAD Systems: A Study in Biologically Inspired Design;Comput. Aided Des.,2012

4. Synergistic Human-Agent Methods for Deriving Effective Search Strategies: The Case of Nanoscale Design;Res. Eng. Des.,2015

5. Lifting the Veil: Drawing Insights About Design Teams From a Cognitively-Inspired Computational Model;Des. Stud.,2015

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