Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis

  • Angelo Oddi
  • Riccardo Rasconi
  • Amedeo Cesta
  • Stephen F. Smith
Article

DOI: 10.1007/s10472-011-9264-8

Cite this article as:
Oddi, A., Rasconi, R., Cesta, A. et al. Ann Math Artif Intell (2011) 62: 371. doi:10.1007/s10472-011-9264-8

Abstract

This paper presents a heuristic algorithm for solving a job-shop scheduling problem with sequence dependent setup times and min/max separation constraints among the activities (SDST-JSSP/max). The algorithm relies on a core constraint-based search procedure, which generates consistent orderings of activities that require the same resource by incrementally imposing precedence constraints on a temporally feasible solution. Key to the effectiveness of the search procedure is a conflict sampling method biased toward selection of most critical conflicts and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically both on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times and by introducing a new benchmark with setups and generalized precedence constraints.

Keywords

Random-restart Constraint-based reasoning Job-shop scheduling Setup times Generalized precedence constraints 

Mathematics Subject Classifications (2010)

68T20 68M20 68W20 

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Angelo Oddi
    • 1
  • Riccardo Rasconi
    • 1
  • Amedeo Cesta
    • 1
  • Stephen F. Smith
    • 2
  1. 1.Istituto di Scienze e Tecnologie della CognizioneConsiglio Nazionale delle RicercheRomeItaly
  2. 2.Robotics InstituteCarnegie Mellon UniversityPittsburghUSA

Personalised recommendations