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Static vs. Dynamic Populations in GAs for Coloring a Dynamic Graph Cara Monical Forrest Stonedahl

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Presentation on theme: "Static vs. Dynamic Populations in GAs for Coloring a Dynamic Graph Cara Monical Forrest Stonedahl"— Presentation transcript:

1 Static vs. Dynamic Populations in GAs for Coloring a Dynamic Graph Cara Monical cmonica2@illinois.edu Forrest Stonedahl forreststonedahl@augustana.edu GECCO ’14 July 16, 2014

2 Imagine You Want To… Allocate RegistersFrequenciesBatches For Conflicting VariablesDevicesJobs In Interpreted Program Mobile Ad Hoc Network Management System

3 Dynamic Graph Coloring GAs for Static Graph Coloring Galinier & Hao ‘99 many others Online Static Graph Coloring Lovász et. al. ‘89 Ant-Based Dynamic Graph Coloring Preuveneers & Berbers ‘04

4 Big Question Dynamic Problem Genetic Algorithm [Jin & Branke ‘05]

5 Genetic Algorithm Population of solutions Evaluate fitness Select fit individuals Perform Crossover Perform Mutation 4 3 5 6 7 2 9 8 10 1 1 2 5 8 7 3 6 9 4 Pop Size: 100 Greedy DecoderTournament, size 3

6 Evaluate fitness Select fit individuals Reproduction: OX1 & SWAP Parent 1 Parent 2 Offspring Population of solutions Perform Crossover Perform Mutation AfterBefore 21435678910 214356789 289 * * 1 43567 298 1 43567 2135689 35674 Rate: 70% Rate: 50% [Starkweather ‘91]

7 Experimental Setup CDEAB 1. Graph 3. Dynamic Population (DGA) 2. DSATUR [Brélaz ‘79] 4. Static Population (SGA) AEBDCDCAEBECDBADAEBCBADCEEDCABADBECECDAB 0 0 0 CBDEAADBECCAEDBAEBCD 4 3 ECDBADABCEDAEBCACDEB 3 4 4 3 3 3 3 3 4 3 A E D C B EDCABCBDEAADBECCAEDBAEBCDECDBADABCEDAEBCACDEB

8 Experimental Setup 1. Graph 3. Dynamic Population (DGA) 2. DSATUR 4. Static Population (SGA) DEBFCFCBEDBDFECBCDFEDBCFE 0 0 3 CBDEAADBECCAEDBAEBCD 4 3 7 6 CBFDEBDECFFCEDBBECFDEBFDCFCEDBBDECFBECFD 6 FCEDBDECFBBDFECBDCFE 3 3 3 3 3 3 3 3 3 A E D C B F BCDFEEBFDCFCEDBBDECFBECFDFCEDBDECFBBDFECBDCFE

9 Experimental Parameters Graph Properties Dynamic Properties n: Size, 100 p: Edge density,.6 Structure G(n,p,c v ) Euclidean cv: Vertex change rate,.01 e: Evolution a step, 1000

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12 .05.025.0167.0125.01.1.033.2.075.15.025.0375.1.03.067.04

13 (Some) Big Answers (For this Problem & Algorithm) Dynamic Problem ≥ Succession of Static Problems 1. Highly Dynamic Problem ≈ Succession of Static Problems 2. Slightly Dynamic Problem > Succession of Static Problems 3.

14 Thank You Centre College Department of Computer Science and Department of Mathematics Centre College, John C. Young Program Contact Information Cara Monical University of Illinois at Urbana-Champaign Math Department cmonica2@illinois.edu Forrest Stonedahl Augustana College CS and Math Departments forreststonedahl@augustana.edu

15 Performance vs. Edge Density G(n,p,c v ) GraphsEuclidean Graphs

16 Performance vs. Evolution G(n,p,c v ) GraphsEuclidean Graphs

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