Ziyuan Sun | Searcharxiv

arXiv2026

Zero-dimensional multi-physics-constrained parameter design and optimization for advanced quasi-isodynamic stellarators

A zero-dimensional (0D) multi-physics-constrained framework for parameter design and optimization of Stable Quasi-Isodynamic Designs (SQuIDs) is presented. Single- and multi-objective optimizations for three staged devices are carried out using an in-house stellarator 0D systems code: YF-1 for discharge demonstration, YF-2 for scientific break even, and YF-3 for a commercial demonstration plant. Pareto searches map the main design trade-offs across the three generations. The equal weight optima for YF-2 and YF-3 both lie in the electron-root favorable regime of the adopted root proxy: YF-2 recovers $Q_{phys} \sim 1$, while YF-3 reaches an ignited point at reactor scale. Future work will couple engineering feasibility and economic assessment modules for integrated plant evaluation.

physics.plasm-ph↗

arXiv2023

A Mixed-integer Linear Formulation for Dynamic Modified Stochastic p-Median Problem in a Competitive Supply Chain Network Design

The Dynamic Modified Stochastic p-Median Problem (DMS-p-MP) is an important problem in supply chain network design, as it deals with the optimal location of facilities and the allocation of demand in a dynamic and uncertain environment. In this research paper, we propose a mixed-integer linear formulation for the DMS-p-MP, which captures the key features of the problem and allows for efficient solution methods. The DMS-p-MP adds two key features to the classical problem: (1) it considers the dynamic nature of the problem, where the demand is uncertain and changes over time, and (2) it allows for the modification of the facility locations over time, subject to a fixed number of modifications. The proposed model is using robust optimization in order to address the uncertainty of demand by allowing for the optimization of solutions that are not overly sensitive to small changes in the data or parameters. To manage the computational challenges presented by large-scale DMS-p-MP networks, a Lagrangian relaxation (LR) algorithm is employed. Our computational study in a real-life case study demonstrates the effectiveness of the proposed formulation in solving the DMS p-Median Problem. According to the results, the number of opened and closed buildings remains unchanged as the time horizon increases. This is due to the periodic nature of our demand. This formulation can be applied to real-world problems, providing decision-makers with an effective tool to optimize their supply chain network design in a dynamic and uncertain environment.

math.OC↗