Improved local search for job shop scheduling with uncertain durations

20Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

This paper is concerned with local search methods to solve job shop scheduling problems with uncertain durations modelled as fuzzy numbers. Based on a neighbourhood structure from the literature, a reduced set of moves and the consequent structure are defined. Theoretical results show that the proposed neighbourhood contains all the improving solutions from the original neighbourhood and provide a sufficient condition for optimality. Additionally, a makespan lower bound is proposed which can be used to discard neighbours. Experimental results illustrate the good performance of both proposals, which considerably reduce the computational load of the local search, as well as a synergy effect when they are simultaneously used. Copyright © 2009, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Cite

CITATION STYLE

APA

González-Rodríguez, I., Vela, C. R., Puente, J., & Hernández-Arauzo, A. (2009). Improved local search for job shop scheduling with uncertain durations. In ICAPS 2009 - Proceedings of the 19th International Conference on Automated Planning and Scheduling (pp. 154–161). https://doi.org/10.1609/icaps.v19i1.13371

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free