Linear semi-infinite programming (LSIP) is a branch of optimisation that focuses on problems where a finite number of decision variables is subject to infinitely many linear constraints. This ...

Roughly, we will cover the following topics (some of them may be skipped depending on the time available). Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear ...

Recently, policy optimization for control purposes has received renewed attention due to the increasing interest in reinforcement learning. In this paper, we investigate the convergence of policy ...

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 ...

Abstract: This paper explores the optimization of the production process based on statistical sampling and integer linear programming. Initially, we designed a sampling inspection plan to help ...

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

We developed, evaluated, and deployed computer software that uses mathematical optimization rather than trial-and-error methods to estimate the nutrient content of ...

A first introduction to probability and statistics. This course will provide background to understand and produce rigorous statistical analysis including estimation, confidence intervals, hypothesis ...