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Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction Read chapter Read first chapter

2011 | OriginalPaper | Chapter

16. Multi-objective Production Systems Optimisation with Investment and Running Cost

Authors : Leif Pehrsson, Amos H. C. Ng, Jacob Bernedixen

Published in: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing

Publisher: Springer London

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Abstract

In recent years simulation-based multi-objective optimisation (SMO) of production systems targeting e.g., throughput, buffers and work-in-process (WIP) has been proven to be a very promising concept. In combination with post-optimality analysis, the concept has the potential of creating a foundation for decision support. This chapter will explore the possibility to expand the concept of introducing optimisation of production system cost aspects such as investments and running cost. A method with a procedure for industrial implementation is presented, including functions for running cost estimation and investment combination optimisation. The potential of applying SMO and post-optimality analysis, taking into account both productivity and financial factors for decision-making support, has been explored and proven to be very beneficial for this kind of industrial application. Evaluating several combined minor improvements with the help of SMO has opened the opportunity to identify a set of solutions (designs) with great financial improvement, which are not feasible to be explored by using current industrial procedures.

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previous chapter Simulation-Based Innovization Using Data Mining for Production Systems Analysis
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Metadata
Title
Multi-objective Production Systems Optimisation with Investment and Running Cost
Authors
Leif Pehrsson
Amos H. C. Ng
Jacob Bernedixen
Copyright Year
2011
Publisher
Springer London
Book
Multi-objective Evolutionary Optimisation for Product Design and Manufacturing

Print ISBN: 978-0-85729-617-7

Electronic ISBN: 978-0-85729-652-8

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-0-85729-652-8_16

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