Research Center
The Center for Engineering Computing and Optimization
The Center for Engineering Computing and Optimization focuses on algorithm research and software development with operations research optimization and scientific and engineering computing as the core, and promotes the implementation and application of relevant technologies in multiple industries and fields such as logistics, aviation, supply chain, and multi-physics simulation (CAX). Based on mathematical optimization and topological optimization algorithms, the center focuses on two research priorities, namely, the research and application of general optimization solvers, and the research and application of multi-physics simulation solvers and industrial software. It is committed to providing standardized and high-efficiency optimization solutions for various industries, endowing the industrial field with powerful simulation and analysis capabilities and accurate optimization decision-making support in key links such as design and manufacturing, and promoting the innovative development and upgrading and transformation of the industrial field.
Our Team
The Center has over 30 members from renowned MIT, Cornell, and PKU, with extensive academic backgrounds and practical experience in innovative theory and algorithm design related to areas like mathematical programming algorithms, aviation scheduling, revenue management, and supply chain operations optimization, enabling the team to handle complex challenges in various applications.
Key Research
In response to the series of challenges faced by traditional nonlinear continuous and discrete optimization algorithms when solving large-scale optimization problems, as well as to address many core technical issues in key technology fields such as new materials, micro-nano materials, intelligent manufacturing, and chip design, this research focuses on in-depth studies of mathematical optimization and topology optimization algorithms.
The general optimization solver is a universal solution for operational optimization problems. It can efficiently solve decision-making optimization problems in application scenarios such as energy and power, factory scheduling, and transportation. Due to its versatility and irreplaceability, the solver is considered the core engine of modern intelligent decision-making and one of the key technologies in the industrial software field. Currently, a self-developed general optimization solver has been created, and a series of related research activities have been conducted.
This research direction of multiphysics simulation industrial software centers around solving coupled partial differential equations for multiphysics problems. It takes into account the interactions among various physical phenomena, including mechanics, thermodynamics, electromagnetism, etc., in order to conduct comprehensive analyses of complex physical systems. At present, research efforts have been dedicated to the development of the OpenCAXPlus software development platform, along with solver algorithms and applications.
