Hybrid agent-based method for scheduling of complex batch processes

Yunfei Chu, Fengqi You*, John M. Wassick

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We propose a hybrid method integrating agent-based modeling and heuristic tree search to solve complex batch scheduling problems. Agent-based modeling describes the batch process and constructs a feasible schedule. To overcome myopic decisions of agents, the agent-based simulation is embedded into a heuristic search algorithm. The heuristic algorithm partially explores the solution space generated by the agent-based simulation. Because global information of the objective function value is used in the search algorithm, the schedule performance is improved. As an efficient scheduling algorithm, the hybrid method is applicable to large-scale complex industrial scheduling problems. Its performance is demonstrated by a complex case study from The Dow Chemical Company.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages940-945
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2014 American Control Conference, ACC 2014
CountryUnited States
CityPortland, OR
Period6/4/146/6/14

Keywords

  • Agents-based systems
  • Optimization
  • Process control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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