Partial design space exploration strategies applied in preliminary design - Richard de Latour, Thomas; Chenouard, Raphaël; Granvilliers, Laurent (International journal on interactive design and manufacturing, 2024)
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.