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Artificiell intelligens och intelligenta system

Certifierbara bevis och justifieringsteknik

Cyber-fysisk systemanalys

Digitalisering av framtidens energi

Formell modellering och analys av inbyggda system

Förnybar energi

Försörjning och skuldsättning

Heterogena system

Industriella AI-system

Industriell programvaruteknik

Innovationsledning

Komplexa inbyggda system i realtid

Learning, Inclusive education, School transitions – for All (LISA)

Lärande och optimering

Modellbaserad konstruktion av inbäddade system

M-TERM - Mälardalen University Team of Educational Researchers in Mathematics

Forskargruppen MIND (Mälardalen INteraction and Didactics)

Personcentrerad vård och kommunikation

Programmeringsspråk

Programvarutestlaboratorium

Samhällsvetenskapernas didaktik och pedagogiska praktiker

Språk- och litteraturvetenskap samt ämnenas didaktik

Statsvetenskap

Stokastiska processer, statistik och finansmatematik

Säkerhetskritisk teknik

Teknisk matematik

Vård, återhämtning och hälsa

EMOPAC - Evolutionary Multi-Objective Optimization and Its Applications in Analog Circuit Design

This project will contribute an efficient software solution for hardware design taking into account different objectives and requirements.

Avslutat

Start

2013-01-01

Avslut

2016-06-30

Huvudfinansiering

Forskningsinriktning

Projektansvarig vid MDU

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Description of the project

The increasing complexity in industrial products and systems entail appropriate optimization methods and automated design techniques. Typical optimization problems in real-world are often computationally hard and subject to multiple, conflicting and non-commensurate objectives. Traditional single-objective optimization techniques only offer one single solution to problems by maximizing/minimizing an overall goal function.

Evolutionary algorithms (EAs) have proved their superiority to traditional optimization methods by their stronger global search ability in complex spaces. EAs are particularly suitable to solve multi-objective problems since they simultaneously process a population of possible solutions, which enabling finding a set of non-dominated tradeoff solutions in a single run. The set of non-dominated solutions can be presented to a decision maker/designer for the final choice based on her/his preference.

The result of the project will be tested and applied in the industrial domain of analog circuit design. Making a “good” circuit is by no means a trivial task. It entails determination of optimal circuit structure together with many numerical parameters for components such as sizing parameters for resistor, reactor, capacitor as well as specifications for the control and protection. Further there are many conflicting objectives and constraints underlying the design procedure, and improving one factor would force others to worsen. This project will contribute an efficient software solution for hardware design taking into account different objectives and requirements.