In 2022, global production of construction materials accounted for more than 7% of total carbon emissions. But how many of ...

Combinatorial optimization and integer programming form the backbone of decision-making models in which discrete choices must be made under constraints. At its core, integer programming specialises in ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

Abstract: This paper presents a robust, real-time linear programming (LP) energy management system (EMS) for gridconnected photovoltaic (PV) microgrids with battery storage and flexible loads. The ...

Abstract: This paper addresses inefficiencies in microchip outbound logistics by balancing transportation and storage costs under real-world constraints. Existing methods rarely integrate dispatch ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

This study presents an optimization method for arranging lattice radiotherapy (LRT) targets to enhance the contrast between peak and valley doses, aiming to improve the treatment effectiveness and ...

This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary data ...

The present paper focuses on the optimization of large-flow coefficient centrifugal compressors, utilizing a mature centrifugal compressor impeller with a flow coefficient of 0.16 under design point ...