Balancing Inventory Management: Genetic Algorithm Optimization for A Novel Dynamic Lot Sizing Model in Perishable Product Manufacturing.

Autor: Leuveano, Raden Achmad Chairdino, Asih, Hayati Mukti, Ridho, Muhammad Ihsan, Darmawan, Dhimas Arief
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Zdroj: Journal of Robotics & Control (JRC); 2023, Vol. 4 Issue 6, p878-895, 18p
Abstrakt: In Indonesia, the significant role of perishable products in food wastage has placed the country fourth globally in household food waste. Managing inventory for such products, with their short shelf life and stringent safety standards, emphasizes the need for efficient lot sizing planning. This study introduces a novel Dynamic Lot-Sizing (DLS) model, addressing perishable products and inventory constraints across multiple products, periods, and varying demands. The model aims to optimize production quantity and binary production, minimizing overall system costs. Employing a Genetic Algorithm (GA), this research solves the DLS model under constrained and unconstrained inventory capacities. Real-case data from a bread manufacturing company validates the model, while sensitivity analysis examines perishability's impact on the solution and model performance. The DLS-GA model not only reduces system costs but also effectively considers product perishability, offering optimal production plans. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index