Work

A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty

Year: 2022

Type: article

Abstract: We seek to optimize the production planning of a three-echelon remanufacturing system under uncertain input data. We consider a multi-stage stochastic integer programming approach and use scenario trees to represent the uncertain information structure. We introduce a new dynamic programming formulation that relies on a partial nested decomposition of the scenario tree. We then propose a new approximate stochastic dual dynamic integer programming algorithm based on this partial decomposition. Our numerical results show that the proposed solution approach is able to provide near-optimal solutions for large-size instances with a reasonable computational effort.

Source: International Journal of Production Research

DOI: 10.1080/00207543.2022.2120924

Authors: Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum

Institutions: Universidad de Santiago de Chile, Université Paris-Saclay, Laboratoire Interdisciplinaire des Sciences du Numérique, Conservatoire National des Arts et Métiers, Centre d'études et de recherche en informatique et communications

Language: English

Topic: Sustainable Supply Chain Management

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: Universidad de Santiago de Chile, Departamento de Investigaciones Científicas y Tecnológicas, Universidad de Santiago de Chile