Skip to Main content Skip to Navigation
Journal articles

A heuristic hybrid framework for vector job scheduling

Abstract : We examine the first phase of a known NP-hard 2-stage assembly problem. It consists of sequencing a set of jobs having multiple components to be processed. Each job has to be worked on independently on a specific machine. We consider these jobs to form a vector of tasks. Our objective is to schedule jobs on the particular machines in order to minimize the completion time before the second stage starts. We first develop a new mathematical programming formulation of the problem and test it on a small problem instance using an integer programming solver. Then, we develop a heuristic algorithm based on Ant Colony Optimization and Variable Neighborhood Search metaheuristics in order to minimize the total completion time. The performance of our implementation appears to be efficient and effective.
Document type :
Journal articles
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03402393
Contributor : Kathleen Torck Connect in order to contact the contributor
Submitted on : Monday, October 25, 2021 - 4:09:23 PM
Last modification on : Wednesday, November 3, 2021 - 5:22:07 AM

Links full text

Identifiers

Collections

Citation

Nareyus I Lawrance Amaldass, Cormac Lucas, Nenad Mladenovic. A heuristic hybrid framework for vector job scheduling. Yugoslav Journal of Operations Research, University of Belgrade, 2017, 27 (1), pp.31-45. ⟨10.2298/YJOR150416013A⟩. ⟨hal-03402393⟩

Share

Metrics

Record views

4