.... Since the suggested formulation is a conventional bi-objective MILP, one can solve the problem (i.e., obtain Pareto front) using various methodologies for multi-objective optimization (e.g., weighted sum method, ε -constraint method [ 74 ]). This section presents two case studies demonstrating...

... generative design machine learning multi-objective optimization Modifying existing designs to generate new ones is an essential aspect of various engineering sectors, such as aerospace, automotive, architecture, pharmaceuticals, consumer goods, and many others. Design modification significantly...

... topologies (PRS, RRS, and internal closed loop) and two layouts (symmetrical and “T” shape). Herein, P, R, and S denote prismatic, rotational, and spherical joints. This article presents the multi-objective optimization of the hybrid robot regarding different limb topology, limb layout, and corresponding...

... classification design optimization machine learning metamodeling multi-objective optimization robust design simulation-based design Fonds Wetenschappelijk Onderzoek 10.13039/501100003130 12ZZP23N Driven by the goal of reducing the computational burden associated with conventional...

...-objective optimization systems design Group behavior is widespread with phenomena like ant colonies, fish swarms, bird flights, and so on. The industry has been inspired by this and developed techniques such as reinforcement learning to make it possible for multi-robot systems to perform complex...

... 01 02 2024 conceptual design design optimization multi-objective optimization packaging optimization Natural Sciences and Engineering Research Council of Canada 10.13039/501100000038 Discovery Grant Multidisciplinary systems design is a complicated and time-intensive...

... in computational investigations for characterizing tissue scaffold design trade-offs and provide a foundation for future design multi-objective optimization for complex biomedical systems. Email: amit.arefin@ttu.edu 1 Corresponding author. Email: paul.egan@ttu.edu Contributed by the Design...

... design optimization engineering design GPU programming interval arithmetic parallel computing design automation design evaluation design visualization multidisciplinary design and optimization multi-objective optimization 17 03 2023 31 07 2023 03 08 2023 06 12 2023...

... for subsystem health monitoring, dynamic Bayesian networks for system reliability analysis, and multi-objective optimization schemes for optimizing system performance. The proposed framework systematically integrates these schemes to enable their application to a wide range of tasks, including offline...

... handling technique multi-objective optimization engineering design evolutionary algorithms design optimization simulation-based design Optimization methods are crucial for engineering design, but not all problems are well-defined or differentiable. Evolutionary algorithms (EAs), a population...

... 11 08 2023 17 08 2023 11 09 2023 design methodology design of engineered materials system design optimization multi-objective optimization National Science Foundation 10.13039/100000001 CMMI 1825444 CMMI 1825521 This paper explores approaches to leverage...

...Homero Valladares; Andres Tovar The solution to global (a posteriori) multi-objective optimization problems traditionally relies on population-based algorithms, which are very effective in generating a Pareto front. Unfortunately, due to the high number of function evaluations, these methods...

... with a multi-objective optimization process. To this end, first, a parametric model for a ring-shaped fourfold origami structure, called the Miura-oRing metastructure, is developed based on appropriate geometric parameters. Its nonlinear folding process is then simulated according to geometric compatibility...

... computationally intensive procedures. To speed up the optimization process and deal with expensive constraints, a new dimension selection-based constrained multi-objective optimization (MOO) algorithm is developed combining least absolute shrinkage and selection operator (LASSO) regression, artificial neural...

...-geometry. This is formulated as a multi-objective optimization problem (MOOP) where the obtained optimal ease-off is guaranteed to be manufacturable. To this end, an original strategy is proposed where the search for the pinion optimal tooth surface happens in the space of the coefficients of a polynomial...

... mechanism synthesis multi-objective optimization A common challenge in mechanical system design is the kinematic synthesis of mechanisms to meet a series of motion tasks. Motion tasks are usually divided into three categories: guiding the rigid body through a series of specified positions...

... was proposed by Deb et al. as a purely multi-objective optimization problem [ 42 ]. However, by treating some objective functions as parameter functions, a parametric test problem is formed that is used to test the hypercone angle. In the purely multi-objective form, the solution is a linear Pareto frontier...

..., there is limited usage of Bayesian frameworks on problems of multi-objective optimization under interval uncertainty. This article seeks to formulate an approach for the solution of these problems via the expected improvement Bayesian acquisition function. In this paper, a method is developed for iteratively...

...Yin Liu; Shuo Wang; Kunpeng Li; Wei Sun; Xueguan Song Most practical multi-objective optimization problems are often characterized by two or more expensive and conflicting objectives, which require time-consuming simulations. Commonly used algorithms construct a surrogate model of each objective...

... Automation Committee of ASME for publication in the J ournal of M echanical D esign . 23 03 2021 05 11 2021 10 11 2021 06 12 2021 design optimization multi-objective optimization simulation-based design topology optimization Topology optimization (TO) has been...