Generation of dispatching rules for job sequencing in singlemachine environments

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

A typical way to schedule a set of jobs is to evaluate and optimize different job sequences and then process them in the best found order. This global optimization approach can be applied for any set of jobs. Unfortunately, optimizing a subset of these jobs requires a new optimization run for this particular subsequence. In this paper we show the generation of dispatching rules that aid job sequencing in single machine environments using genetic programming and delta features. The rules are applied to sets of jobs and yield priorities depending on certain characteristics. These priorities are then used to create job orders dynamically depending on the last executed job. Once generated for specific scenarios, the rules provide on-the-fly sequence generation capability for queued subsets of jobs. Finally, we compare the performance and robustness of the generated rules against the scheduling approach.

Original languageEnglish
Title of host publication28th European Modeling and Simulation Symposium, EMSS 2016
EditorsAgostino G. Bruzzone, Emilio Jimenez, Loucas S. Louca, Lin Zhang, Francesco Longo
PublisherDIME UNIVERSITY OF GENOA
Pages117-121
Number of pages5
ISBN (Electronic)9788897999683
Publication statusPublished - 2016
Event28th European Modeling and Simulation Symposium, EMSS 2016 - Larnaca, Cyprus
Duration: 26 Sep 201628 Sep 2016

Publication series

Name28th European Modeling and Simulation Symposium, EMSS 2016

Conference

Conference28th European Modeling and Simulation Symposium, EMSS 2016
CountryCyprus
CityLarnaca
Period26.09.201628.09.2016

Keywords

  • Dispatching rules
  • Genetic algorithms
  • Genetic programming
  • Scheduling
  • Sequence optimization
  • Single-machine

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