A multi-objective optimisation suite for Tecnomatix Plant Simulation

Date
2018-12
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: This thesis presents the development of an optimisation suite for a commercial, discrete-event simulation software package. It is demonstrated in this work that the capabilities of the simulation software are limited in the context of stochastic multi-objective optimisation problems and can, thus, be improved using existing knowledge in the literature. The suite developed in this work utilises, therefore, modern and more effective techniques from the literature to tackle stochastic multi-objective optimisation problems. Its purpose is that of being a third-party multi-objective optimisation solver that can be integrated with the commercial discrete-event simulation software in order to assist it in its limitations. The suite is validated using well-known problems in the literature and the relevance of the solution approach proposed in this thesis is demonstrated.
AFRIKAANSE OPSOMMING: Hierdie tesis handel oor die ontwikkeling van 'n optimeringsuite vir 'n kommersi ële sagtewarepakket wat diskrete gebeure simuleer (oftewel \DES"-sagteware). Die studie toon dat die funksies van die DES-sagteware beperk is in die konteks van stogastiese optimeringsprobleme met veelvuldige doelwitte, en dat dit met behulp van bestaande kennis in die literatuur verbeter kan word. Daarom gebruik die suite wat in die studie ontwikkel is moderne en doeltreffender tegnieke uit die literatuur om stogastiese optimeringsprobleme met veelvuldige doelwitte die hoof te bied. Die doel is dat die suite as 'n derdepartyoplosser van optimeringsprobleme met veelvuldige doelwitte moet dien wat by die kommersiële DES-sagteware geïntegreer kan word en sodoende die beperkinge daarvan te bowe kan kom. Die suite word met bekende probleme in die literatuur gestaaf en die relevansie van die voorgestelde oplossingsbenadering word aangetoon.
Description
Thesis (MEng)--Stellenbosch University, 2018.
Keywords
Multiple criteria decision making, UCTD, Metaheuristics, Optimization, Robust
Citation