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Spatial and Temporal Visualisation of Evolutionary Algorithm Decisions in Water Distribution Network Optimisation

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GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

Pages 941 - 948

https://doi.org/10.1145/2739482.2768442

Published: 11 July 2015 Publication History

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Abstract

Much research has been conducted into the visualisation of objective space and decision space landscapes. This work moves away from this and investigates a 3D interactive method for linking EA decisions through time with the design of engineering systems. The proposed system shows through an intuitive interface, the design space being explored by the algorithm including decision variable choices, locations that are fixed early on in the optimisation and those problem areas that are difficult for the algorithm to solve. The paper presents a case study in water distribution network design, although the methods described are, in principle, generalisable to other design domains.

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Cited By

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Walker DCraven M(2020)Identifying good algorithm parameters in evolutionary multi- and many-objective optimisationApplied Soft Computing10.1016/j.asoc.2019.10590288:COnline publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1016/j.asoc.2019.105902
Medvet EVirgolin MCastelli MBosman PGonçalves ITušar T(2018)Unveiling evolutionary algorithm representation with DU mapsGenetic Programming and Evolvable Machines10.1007/s10710-018-9332-519:3(351-389)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s10710-018-9332-5
Walker DCraven M(2018)Toward the Online Visualisation of Algorithm Performance for Parameter SelectionApplications of Evolutionary Computation10.1007/978-3-319-77538-8_38(547-560)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_38

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Spatial and Temporal Visualisation of Evolutionary Algorithm Decisions in Water Distribution Network Optimisation

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Published In

GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

July 2015

1568 pages

ISBN:9781450334884

DOI:10.1145/2739482

Editor:
Sara Silva
Universidade de Lisboa, Portugal
,
General Chair:
Anna I. Esparcia-Alcázar
Universitat Politècnica de València, Spain

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 July 2015

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GECCO '15

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SIGEVO

GECCO '15: Genetic and Evolutionary Computation Conference

July 11 - 15, 2015

Madrid, Spain

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Walker DCraven M(2020)Identifying good algorithm parameters in evolutionary multi- and many-objective optimisationApplied Soft Computing10.1016/j.asoc.2019.10590288:COnline publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1016/j.asoc.2019.105902
Medvet EVirgolin MCastelli MBosman PGonçalves ITušar T(2018)Unveiling evolutionary algorithm representation with DU mapsGenetic Programming and Evolvable Machines10.1007/s10710-018-9332-519:3(351-389)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s10710-018-9332-5
Walker DCraven M(2018)Toward the Online Visualisation of Algorithm Performance for Parameter SelectionApplications of Evolutionary Computation10.1007/978-3-319-77538-8_38(547-560)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_38

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An analysis of the interface between evolutionary algorithm operators and problem features for water resources problems. A case study in water distribution network design

A micro niche evolutionary algorithm with lower-dimensional-search crossover for optimisation problems with constraints

Comparative Analysis of Evolutionary Algorithms for the Problem of Parametric Optimization of PID Controllers