Bio-control in mushroom farming using a Markov network EDA

Yanghui Wu*, John McCall, Paul Godley, Alexander Brownlee, David Cairns, Julie Cowie

*Corresponding author for this work

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

2 Citations (Scopus)


In this paper we present an application of an Estimation of Distribution Algorithm (EDA) that uses a Markov network probabilistic model The application is to the problem of bio-control in mushroom farming, a domain which admits bang-bang-control solutions. The problem is multiobjective and uses a weighted fitness function. Previous work on this problem has applied genetic algorithms (GA) with directed intervention crossover schemes aimed at effective biocontrol at an efficient level of intervention. Here we compare these approaches with the EDA Distribution Estimation Using Markov networks (DEUMd). DEUM d constructs a probabilistic model using Markov networks. Our experiments compare the quality of solutions produced by DEUMd with the GA approaches and also reveal interesting differences in the search dynamics that have implications for algorithm design.

Original languageEnglish
Title of host publication2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)
Number of pages6
ISBN (Print)9781424418220
Publication statusPublished - 23 Sep 2008
Externally publishedYes
Event2008 IEEE Congress on Evolutionary Computation: CEC 2008 - Hong Kong, China
Duration: 1 Jun 20086 Jun 2008

Publication series

Name2008 IEEE Congress on Evolutionary Computation, CEC 2008
ISSN (Print)1089-778X
ISSN (Electronic)1941-0026


Conference2008 IEEE Congress on Evolutionary Computation
CityHong Kong

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science


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