Improved Local Search for Job Shop Scheduling with uncertain Durations

Authors

  • Ines Gonzalez-Rodriguez University of Cantabria
  • Camino Vela University of Oviedo
  • Jorge Puente University of Oviedo
  • Alejandro Hernandez-Arauzo University of Oviedo

DOI:

https://doi.org/10.1609/icaps.v19i1.13371

Keywords:

artificial intelligence, scheduling, job shop, uncertainty, fuzzy, local search

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.

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Published

2009-10-16

How to Cite

Gonzalez-Rodriguez, I., Vela, C., Puente, J., & Hernandez-Arauzo, A. (2009). Improved Local Search for Job Shop Scheduling with uncertain Durations. Proceedings of the International Conference on Automated Planning and Scheduling, 19(1), 154-161. https://doi.org/10.1609/icaps.v19i1.13371