Partial design space exploration strategies applied in preliminary design

During preliminary phases in product design, on the basis of strong physical hypotheses (e.g. isotherm, steady state), physical and functional requirements can be expressed as coarse-grained constraint-based models on a few degrees of freedom, possibly including several design criteria to optimize....

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Bibliographic Details
Published in:International journal on interactive design and manufacturing Vol. 18; no. 4; pp. 2291 - 2307
Main Authors: Richard de Latour, Thomas, Chenouard, Raphaël, Granvilliers, Laurent
Format: Journal Article
Language:English
Published: Paris Springer Paris 01.05.2024
Springer Nature B.V
Springer Verlag
Subjects:
Algorithms
Boxes
CAE) and Design
Computer Science
Computer-Aided Engineering (CAD
Decision making
Design
Design criteria
Design engineering
Design optimization
Electronics and Microelectronics
Energy consumption
Engineering
Engineering Design
Engineering Sciences
Genetic algorithms
Hypotheses
Industrial Design
Instrumentation
Mechanical Engineering
Multiple objective analysis
Optimization
Original Paper
Preliminary designs
Product design
Solvers
Space exploration
Variables
Numerical constraint satisfaction problem
Preliminary design
Anytime branch-and-prune algorithm
Multi-objective optimization
Design space exploration
Design space exploration numerical constraint satisfaction problem anytime branch-and-prune algorithm multi-objective optimization preliminary design
anytime branch-and-prune algorithm
multi-objective optimization
preliminary design
numerical constraint satisfaction problem
ISSN:1955-2513, 1955-2505
Online Access:Get full text
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Summary:During preliminary phases in product design, on the basis of strong physical hypotheses (e.g. isotherm, steady state), physical and functional requirements can be expressed as coarse-grained constraint-based models on a few degrees of freedom, possibly including several design criteria to optimize. Such models are usually handled by multi-objective optimization solvers in order to find design solutions giving the best trade-offs between design criteria. Another approach developed in this paper is to partially explore all the areas of the design space using an anytime interval branch-and-prune algorithm called IDFS such that the design criteria are converted into so-called ε -constraints. The expected result is a sample of solutions diversified in both the objective space and the design space. Several quality indicators are introduced in order to measure this diversity and compare IDFS with two state-of-the-art multi-objective optimization solvers NSGA-II and NSGA-III on three real-world case studies. The results show that IDFS is able to identify new close-to-optimal designs and permits a better understanding of the design space. This framework provides a promising alternative tool for decision making, in particular for integrating interaction in the preliminary design process. Graphical Abstract Partial exploration aims to compute a diversified subset of feasible solutions; We built an anytime branch and prune algorithm for partial design space exploration. We built a protocol to analyze diversity in both the design and the objective space. We compare partial exploration and optimization approaches on three design problems. Partial Exploration is a tool for decision makers to identify quasi-optimal designs.
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ISSN:1955-2513
1955-2505
DOI:10.1007/s12008-023-01377-7