Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 229

The DOI matches its Crossref record.

Quantitative models for inventory and production planning in closed-loop supply chains

Akçalı, E., Çetinkaya, S.·2011·International Journal of Production Research

Abstract

The increased popularity of remanufacturing requires firms to rethink their supply chain systems and explore new avenues for the coordination of forward and reverse supply chains to transform existing supply chain systems into closed-loop supply chain (CLSC) systems. Several issues encountered in remanufacturing create unique operational challenges that must be taken into account in specifying guidelines for inventory and production planning (I&PP) for CLSC systems. These challenges provide a rich context for novel optimisation problems. Consequently, the literature on I&PP for CLSC systems has been growing continually. In this paper, we review the existing quantitative literature on I&PP for CLSC systems. We broadly categorise the present work into deterministic and stochastic problems according to the modelling of demand and return processes. Upon identifying the important relevant modelling parameters that influence the complexity of the underlying models, we provide a comprehensive classification of the current work according to these parameters. In addition, we highlight the solution methodologies used in the literature. Our goals are twofold: to provide a comprehensive exposition of the state-of-art in quantitative models for I&PP for CLSC systems, and to identify new avenues of research in I&PP that will aid in the practical implementation of remanufacturing.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/00207541003692021

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 229

Metadata

Authors
Akçalı, E., & Çetinkaya, S.
Venue
International Journal of Production Research
Published
2010-04-29
Volume
49
Issue
8
Pages
2373-2407
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2039837125
Cited by
229
References
0
FWCI
31.84
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Quantitative models for inventory and production planning in closed-loop supply chains. https://app.cochat.ai/papers/10.1080/00207541003692021
The paper
Akçalı, E., & Çetinkaya, S. (2011). Quantitative models for inventory and production planning in closed-loop supply chains. International Journal of Production Research. https://doi.org/10.1080/00207541003692021

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.