Overview:  Covers the most frequently asked dynamic programming questions in coding interviews.Explains the core DP patterns used by Google, Amazon, Meta, ...

Planning for promotions is far harder than planning for routine demand and replenishment. The solution lies in a hybrid ...

Key Laboratory of Optimization Theory and Applications, School of Mathematical Sciences, China West Normal University, Nanchong, China. Overall, existing literature mainly focuses on smooth ...

Abstract: dynamic multiobjective optimization (DMO) problems are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

Abstract: Eco-driving has emerged as a promising approach to reducing fuel consumption in road vehicles by optimizing driving behavior for enhanced system efficiency. This paper formulates the ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

A quantum computer can solve optimization problems faster than classical supercomputers, a process known as "quantum advantage" and demonstrated by a USC researcher in a paper recently published in ...