A Novel Approach to Cost Estimation in Lot Sizing with Uncertain Lead Times

The lot sizing problem involves meeting the demand of the clients of a given retailer by placing orders with different suppliers. Decision-making models were developed to minimize the retailer’s total cost while considering their retailers’ different characteristics, such as their capacities, prices, and lead times. However, when integrating uncertainty into the environment, this challenging problem becomes even more complex, and the exact methods developed need extremely long computational time to go over all the possible scenarios. This paper proposed a novel formulation to minimize the operations needed when finding the optimal solution to the lot sizing problem under uncertain lead times.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.09.063
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
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article

A Novel Approach to Cost Estimation in Lot Sizing with Uncertain Lead Times

Manuella Germanos, Grégory Zacharewicz, Oussama Ben-Ammar
IFAC-PapersOnLine
Advanced Manufacturing and Logistics Optimization
article

A Novel Approach to Cost Estimation in Lot Sizing with Uncertain Lead Times

Manuella Germanos, Grégory Zacharewicz, Oussama Ben-Ammar
article en

Abstract

The lot sizing problem involves meeting the demand of the clients of a given retailer by placing orders with different suppliers. Decision-making models were developed to minimize the retailer’s total cost while considering their retailers’ different characteristics, such as their capacities, prices, and lead times. However, when integrating uncertainty into the environment, this challenging problem becomes even more complex, and the exact methods developed need extremely long computational time to go over all the possible scenarios. This paper proposed a novel formulation to minimize the operations needed when finding the optimal solution to the lot sizing problem under uncertain lead times.

IFAC-PapersOnLineVol. 59(10)
Université de Montpellier (FR), IMT Mines Alès (FR), EuroMov Digital Health in Motion
Openalex Percentile: Top 63%
Advanced Manufacturing and Logistics Optimization
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