Improved population-based incremental learning algorithm for scheduling multi-bridge waterjet cutting processes

Xianghu Meng, Jun Li, Mengchu Zhou, Xianzhong Dai

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

7 Scopus citations

Abstract

An improved population-based incremental learning (IPBIL) algorithm is proposed to plan collision-free cutting paths of multi-bridge water-jet cutting processes. Multi-bridge waterjet cutting machines (MWCM) are one of the preferred solutions for cutting large-size flat work pieces. The work areas of two adjacent bridges with a waterjet head are designed to overlap with each other in an MWCM to ensure no dead zones of cutting. It means that a pair of adjacent bridges may crash with each other over their overlapped area and result in damages of the machine. It is an interference problem that one must solve for MWCM. Due to a great number of curves to be cut in a large process area of MWCM, it needs to optimize the cutting routes of the bridges. This paper proposes an IPBIL-based integrated method for solving both the interference and routing problems. The validity of the presented method is confirmed with a case study.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
PublisherIEEE Computer Society
Pages496-500
Number of pages5
ISBN (Print)9781479931064
DOIs
StatePublished - Jan 1 2014
Event11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 - Miami, FL, United States
Duration: Apr 7 2014Apr 9 2014

Publication series

NameProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Other

Other11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
CountryUnited States
CityMiami, FL
Period4/7/144/9/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering

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