Abstract: To address the challenges posed by non-convex optimization in path planning for intelligent vehicles using numerical optimization techniques, this study introduces a combined approach ...

In trajectory optimization, there are two prevalent optimizers which is Differential Dynamic Programming (DDP) and Sequential Quadratic Programming. I want to compare the computation speed between the ...

Abstract: Various discrete-time zeroing neural network (DTZNN) models have been developed for solving dynamic constrained quadratic programming. However, two challenges persist within the DTZNN ...

Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...

QIHD (Quantum-Inspired Hamiltonian Descent) is a quantum-inspired, GPU-enabled algorithmic framework for solving mixed-integer quadratic programming (MIQP) problems. MIQP is a classic optimization ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...