Abstract: This letter presents an integer programming framework for partitioning a linear array into contiguous, non-overlapping subarrays while minimizing their total number. The proposed method ...

A new technical paper titled “PPA-Aware Tier Partitioning for 3D IC Placement with ILP Formulation” was published by researchers at Seoul National University and Ulsan National Institute of Science ...

Lawmakers in Harrisburg are looking at bills to tackle dynamic pricing. Consumers see dynamic prices on purchases like airfare, hotel rooms and concert tickets. It means when there's high demand and ...

Abstract: Multi-robot planning and coordination in uncertain environments is a fundamental computational challenge, since the belief space increases exponentially with the number of robots. In this ...

ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...

Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India Indian Institute of Technology Delhi-Abu Dhabi, Khalifa City B 20010, Abu Dhabi, UAE ...

Welcome to Play Smart, a regular GOLF.com game-improvement column that will help you become a smarter, better golfer. To generate your maximum power, you’ve got to know how to properly shift your ...

We combine Mixed-Integer Programming (MIP) with Machine Learning to find near-optimal portfolios efficiently: maximize: μᵀw - λ·(wᵀΣw) - transaction_costs(w, w_prev) subject to: 1. Σwᵢ = 1 (budget ...

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 ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Integer programming, a cornerstone of combinatorial optimisation, focuses on the selection of discrete decision variables to solve complex real‐world problems such as scheduling, network design and ...

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...