The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

ABSTRACT: 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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...

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 ...

Prior to PILOT, fitting linear model trees was slow and prone to overfitting, especially with large datasets. Traditional regression trees struggled to capture linear relationships effectively. Linear ...

A Comprehensive Linear Programming Solver Program, Incorporating Diverse Algorithms: Graphical Method, Dantzig's Simplex Method, Bland's Simplex Method, Two-Phase Simplex Method, Dual Method, Dual ...

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Abstract: The rise in private vehicles has led to the rise in the demand for parking, and this demand calls for the need of existing parking areas to be fully optimized in order to accommodate as much ...