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Environmental social science / Urban studies and planning / Cybernetics / Multi-objective optimization / Sustainable development / Sustainable city / Genetic algorithm / Environment / Mathematical optimization / Sustainability


Evolutionary Computing for Multi-Objective Spatial Optimisation Daniel Caparros-Midwood, Stuart Barr and Richard Dawson School of Civil Engineering and Geosciences, Newcastle University Summary During the transition to m
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Document Date: 2015-04-19 18:19:55


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City

Reading / London / Middlesbrough / /

Company

John Wiley & Sons Ltd / /

Country

United Kingdom / /

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Event

Environmental Issue / Natural Disaster / /

Facility

University of Newcastle / Newcastle University / /

IndustryTerm

crossover operator / particular optimal solution / adaptation solutions / median solution / point crossover algorithm / cross product / genetic algorithm / travel costs / spatial decision support tool / decision support tool / transport energy costs / mutation operator / selection operator / increased travel costs / energy / /

NaturalFeature

Tees Valley / /

Organization

Middlesbrough Borough Council / School of Civil Engineering / Middlesbrough Council / office of National Statistics / Richard Dawson School of Civil Engineering and Geosciences / Newcastle University / UK’s Environmental Agency / University of Newcastle / UK Engineering and Physical Sciences Research Council / /

Person

Ordnance Survey / Ordnance Survey Meridian / Daniel Caparros-Midwood / Stuart Barr / Richard Dawson / /

Position

senior lecturer / Chair / /

ProvinceOrState

Holderness / /

PublishedMedium

Machine Learning / IEEE Transactions on Evolutionary Computation / /

Technology

Multi-Objective Optimization using Evolutionary Algorithms / Remote Sensing / genetic algorithm / 2 Genetic Algorithm / Machine Learning / two point crossover algorithm / /

URL

www.ncl.ac.uk/ceser / /

SocialTag