Reducing waste in manufacturing operations: bi-objective scheduling on a single-machine with coupled-tasks - Mines Saint-Étienne Access content directly
Journal Articles International Journal of Production Research Year : 2020

Reducing waste in manufacturing operations: bi-objective scheduling on a single-machine with coupled-tasks

Abstract

This study addresses a scheduling problem involving a single-machine with coupled-tasks and bi-objective optimisation considering simultaneously inventory and environmental waste. A Mixed Integer Linear Program representing the problem is first developed. Subsequently, a Genetic Algorithm (GA) is presented, followed by numerical experiments on multiple instances. Pareto fronts are determined using the ϵ-constraint and weighted sum methods, and a trade-off point is selected according to a distance criterion. Numerical experiments on both small and large instances show near-optimal results for small instances, and considerably reduced computing times for large ones when using the GA. The results show that a compromise can be found, with a decrease in setup-related waste up to 36% for an increase of inventory of 12%. This will help decision-makers to better consider the environmental aspect when designing schedules, as well as reduce their production environmental impact and waste-management costs.
Fichier principal
Vignette du fichier
IJPR submission TPRS-2019-IJPR-0111.pdf (602.51 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Licence : CC BY - Attribution

Dates and versions

emse-02360718 , version 1 (14-09-2023)

Identifiers

Cite

Corentin Le Hesran, Aayush Agarwal, Anne-Laure Ladier, Valerie Botta-Genoulaz, Valérie Laforest. Reducing waste in manufacturing operations: bi-objective scheduling on a single-machine with coupled-tasks. International Journal of Production Research, 2020, 58 (23), pp.7130-7148. ⟨10.1080/00207543.2019.1693653⟩. ⟨emse-02360718⟩
72 View
19 Download

Altmetric

Share

Gmail Facebook X LinkedIn More