Przewozniczek, M.W., Dziurzanski, P., Zhao, S. et al. (1 more author) (2021) Multi-Objective parameter-less population pyramid for solving industrial process planning problems. Swarm and Evolutionary Computation, 60. 100773. ISSN 2210-6502
Abstract
Evolutionary methods are effective tools for obtaining high-quality results when solving hard practical problems. Linkage learning may increase their effectiveness. One of the state-of-the-art methods that employ linkage learning is the Parameter-less Population Pyramid (P3). P3 is dedicated to solving single-objective problems in discrete domains. Recent research shows that P3 is highly competitive when addressing problems with so-called overlapping blocks, which are typical for practical problems. In this paper, we consider a multi-objective industrial process planning problem that arises from practice and is NP-hard. To handle it, we propose a multi-objective version of P3. The extensive research shows that our proposition outperforms the competing methods for the considered practical problem and typical multi-objective benchmarks.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Keywords: | Multi-objective genetic algorithms; Linkage learning; Parameter-less population pyramid; Process manufacturing optimisation |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Sep 2023 15:35 |
Last Modified: | 27 Sep 2023 15:35 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.swevo.2020.100773 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203709 |