Published: 29 September 2023| Version 1 | DOI: 10.17632/pggm5wvg2n.1
Luis Rocha


The capacitated lot-sizing problem with product recovery (CLSP-RM) holds significant importance in reverse logistics but is notoriously complex (NP-hard). In this study, two techniques are introduced to confront this challenge. The first technique entails devising a linear optimization task that eliminates capacity limitations across a wide problem spectrum, yielding a remarkably accurate approximation of the optimal solution (Model A). This adaptable approach presents a potent alternative and holds potential for extension to diverse problem categories owing to its versatile nature. The second technique (Model B) employs a simulation methodology utilizing Halton’s uniform random numbers to address the issue. This randomized production search method sidesteps considerations of production costs, inventory expenditures, and production order when determining production batches . Here are the input data and solution of each instance solved with model A and model B respectively. There are about 4000 instances.


Steps to reproduce

The instances are strictly randomly generated under the assumptions of the paper. All steps that are necessary are described in the paper.


Europa-Universitat Viadrina Wirtschaftswissenschaftliche Fakultat


Constrained Optimization