A bio-inspired evolution-development method for modelling and optimisation of buffer allocation in unreliable serial production line

Z. Zhao, P. Goodall, A. West, A. Colligan, I. Friel, S. Hickinbotham, M. Price, Y. Jin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A buffer is an important element in a production line and its allocation influences the throughput and inventory of the line. The buffer allocation problem can be framed as a multi-objective optimisation problem and is often addressed by using meta-heuristic algorithms, such as evolutionary algorithms. However, these algorithms primarily focus on the “genetic evolution” aspect and do not take in to account the impact of the biological “organism development” process, potentially constraining the exploration of the solution space. In this paper, a bio-inspired evolution-development (evo-devo) approach for modelling and optimising buffer allocations is proposed. The organism representing a production line is defined and modelled, and the evolution and development processes of organisms are developed for researching optimised solutions. The method has been validated by a simulation of a buffer allocation optimisation in an unreliable serial production line with multi-objectives, aiming to maximize production throughput and minimize the total buffer size. Results show that the
proposed method can efficiently obtain solutions, while also achieving greater exploration of the solution space than competing evolutionary algorithms such as the Non-Dominated Sorting Genetic Algorithm II. The proposed approach’s functionality means that it could be applied to other areas of generative design of future factories.
Original languageEnglish
Title of host publication3rd International Conference on Mechanical, Aerospace and Automotive Engineering (CMAAE 2023): Proceedings
PublisherInstitution of Engineering and Technology (IET)
Number of pages6
ISBN (Electronic)9781837240753
DOIs
Publication statusPublished - 31 May 2023
Event3rd International Conference on Mechanical, Aerospace and Automotive Engineering: CMAAE2023 - Nanjing, China
Duration: 08 Dec 202310 Dec 2023
https://www.cmaae.org/his2023

Conference

Conference3rd International Conference on Mechanical, Aerospace and Automotive Engineering
Abbreviated titleCMAAE2023
Country/TerritoryChina
CityNanjing
Period08/12/202310/12/2023
Internet address

Keywords

  • Evolution-development
  • optimisation
  • buffer
  • Multi-objective optimisation

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