Linear mixed model-based approaches have emerged as a more efficient methodology for the analysis of MET data. Recently, these mixed model approaches have become predominant, as they provide a ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...

This notebook serves as an introduction to Linear Programming and MILP with Python, covering both the concepts and practical applications through various popular optimization problems.

About A simple algorithmic implementation of some of the most common lineal programming transport methods and transportation models.

Bounds and approximate formulae are developed for the average optimum distance of the transportation linear programming (TLP) problem with homogeneously, but randomly distributed points and demands in ...

Stochastic transportation problems attract much attention in many fields, such as resource allocation, production management, etc. In this paper, after analyzing how to process random constraints in ...

Unlike the majority of the LCA studies which use average values to linearly estimate marginal water use, the results using the transportation model show a non-linear relationship between marginal ...