Nuevo modelo para el dimensionamiento de lotes de pedidos en funci\'on del volumen de compra y deterioro temporal de los art\'iculos

TL;DR

This paper introduces a comprehensive simulation model for determining optimal order lot sizes in Material Requirements Planning, considering purchase volume and item deterioration, and compares its efficiency to heuristic methods.

Contribution

The paper presents a novel exhaustive enumeration model that explores all supply strategies for optimal lot sizing, improving accuracy over heuristic approaches.

Findings

Model finds the global minimum cost efficiently.

Exhaustive enumeration outperforms heuristics in accuracy.

Validation confirms the model's effectiveness in complex scenarios.

Abstract

This research presents the development of a new simulation model to determine the optimal order lot sizes in Material Requirements Planning, based on purchase volume and the temporal deterioration of items. The scientific novelty lies in the exhaustive enumeration of all supply strategies, considering when and how much raw material and/or inputs to acquire while simultaneously managing multiple factors. The developed model enables obtaining and visualizing all feasible solutions, though a significant challenge arises when dealing with larger planning horizons. The methodology includes formulating a mathematical equation to calculate the total cost of all supply strategies, taking into account quantity discounts and the maximum allowable shelf life of inventory items. The results demonstrate that the model thoroughly explores the entire search space and identifies the optimal solution. Validation is conducted using the tabu search heuristic, a widely recognized optimization technique. While the heuristic converges toward the global minimum, it requires a significantly higher computational load. In contrast, the developed model identifies the global minimum with fewer calculations, showcasing its efficiency and accuracy.