The University of Southampton
University of Southampton Institutional Repository

Efficient local search heuristics for packing irregular shapes in two-dimensional heterogeneous bins

Efficient local search heuristics for packing irregular shapes in two-dimensional heterogeneous bins
Efficient local search heuristics for packing irregular shapes in two-dimensional heterogeneous bins
In this paper we proposed a local search heuristic and a genetic algorithm to solve the two-dimensional irregular multiple bin-size bin packing problem. The problem consists of placing a set of pieces represented as 2D polygons in rectangular bins with different dimensions such that the total area of bins used is minimized. Most packing algorithms available in the literature for 2D irregular bin packing consider
single size bins only. However, for many industries the material can be supplied in a number of standard size sheets, for example, metal, foam, plastic and timber sheets. For this problem, the cut plans must decide the set of standard size stock sheets as well as which pieces to cut from each bin and how to arrange them in order to minimise waste material. Moreover, the literature constrains the orientation of pieces to a single or finite set of angles. This is often an artificial constraint that makes the solution space easier to navigate. In this paper we do not restrict the orientation of the pieces. We show that the local search heuristic and the genetic algorithm can address all of these decisions and obtain good
solutions, with the local search performing better. We also discuss the effect of different groups of stock sheet sizes.
Irregular shapes, Multiple bin size bin packing, Jostle Algorithm
557-571
Springer
Abeysooriya, Ranga, Prasad
4959e73f-5c25-40a1-9bfa-a5023d113562
Bennell, Julia
38d924bc-c870-4641-9448-1ac8dd663a30
Martinez Sykora, Antonio
2f9989e1-7860-4163-996c-b1e6f21d5bed
Bektas, Tolga
Coniglio, Stefano
Martinez-Sykora, Antonio
Boss, Stefan
Abeysooriya, Ranga, Prasad
4959e73f-5c25-40a1-9bfa-a5023d113562
Bennell, Julia
38d924bc-c870-4641-9448-1ac8dd663a30
Martinez Sykora, Antonio
2f9989e1-7860-4163-996c-b1e6f21d5bed
Bektas, Tolga
Coniglio, Stefano
Martinez-Sykora, Antonio
Boss, Stefan

Abeysooriya, Ranga, Prasad, Bennell, Julia and Martinez Sykora, Antonio (2017) Efficient local search heuristics for packing irregular shapes in two-dimensional heterogeneous bins. Bektas, Tolga, Coniglio, Stefano, Martinez-Sykora, Antonio and Boss, Stefan (eds.) In Computational Logistics: 8th International Conference, ICCL 2017, Southampton, UK, October 18-20, 2017, Proceedings. vol. 10572, Springer. pp. 557-571 . (doi:10.1007/978-3-319-68496).

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper we proposed a local search heuristic and a genetic algorithm to solve the two-dimensional irregular multiple bin-size bin packing problem. The problem consists of placing a set of pieces represented as 2D polygons in rectangular bins with different dimensions such that the total area of bins used is minimized. Most packing algorithms available in the literature for 2D irregular bin packing consider
single size bins only. However, for many industries the material can be supplied in a number of standard size sheets, for example, metal, foam, plastic and timber sheets. For this problem, the cut plans must decide the set of standard size stock sheets as well as which pieces to cut from each bin and how to arrange them in order to minimise waste material. Moreover, the literature constrains the orientation of pieces to a single or finite set of angles. This is often an artificial constraint that makes the solution space easier to navigate. In this paper we do not restrict the orientation of the pieces. We show that the local search heuristic and the genetic algorithm can address all of these decisions and obtain good
solutions, with the local search performing better. We also discuss the effect of different groups of stock sheet sizes.

Text
ICCL17_paper_43 - Accepted Manuscript
Download (729kB)

More information

e-pub ahead of print date: October 2017
Published date: October 2017
Keywords: Irregular shapes, Multiple bin size bin packing, Jostle Algorithm

Identifiers

Local EPrints ID: 415314
URI: http://eprints.soton.ac.uk/id/eprint/415314
PURE UUID: e654d0b7-af4b-43c1-86e1-635828997331
ORCID for Antonio Martinez Sykora: ORCID iD orcid.org/0000-0002-2435-3113

Catalogue record

Date deposited: 07 Nov 2017 17:30
Last modified: 16 Mar 2024 05:53

Export record

Altmetrics

Contributors

Author: Ranga, Prasad Abeysooriya
Author: Julia Bennell
Editor: Tolga Bektas
Editor: Stefano Coniglio
Editor: Antonio Martinez-Sykora
Editor: Stefan Boss

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×