Heuristics for the Single-Item Dynamic Lot-Sizing Problem with Rework of Internal Returns

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Abstract

While external product returns from customers are well-studied in the dynamic lot-sizing literature, the same is not true for internal returns resulting from imperfect production. We approach this problem by considering a basic dynamic single-product lot-sizing model in which some of the items produced do not meet quality requirements and, therefore, must be reworked. The objective is to minimize the sum of setup and inventory costs for new production and rework while fully satisfying demand. To this end, three heuristics are developed, based essentially on two production policies that can efficiently coordinate new production and rework for different parameter constellations. This is confirmed by a computational study in which the developed heuristics yielded highly competitive results compared to those obtained with a commercial solver.

Details

OriginalspracheEnglisch
TitelComputational Logistics - 13th International Conference, ICCL 2022, Proceedings
Redakteure/-innenJesica de Armas, Helena Ramalhinho, Stefan Voß
Seiten425-440
Seitenumfang16
Band13557
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa

Externe IDs

Scopus 85138783346
Mendeley 05258e63-5ddf-347f-968b-94f08425d2c0
ORCID /0000-0003-4711-2184/work/142252517