The University of Southampton
University of Southampton Institutional Repository

An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem

An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem
An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem
This paper introduces a new neighborhood search technique, called dynasearch, that uses dynamic programming to search an exponential size neighborhood in polynomial time. While traditional local search algorithms make a single move at each iteration, dynasearch allows a series of moves to be performed. The aim is for the lookahead capabilities of dynasearch to prevent the search from being attracted to poor local optima.
We evaluate dynasearch by applying it to the problem of scheduling jobs on a single machine to minimize the total weighted tardiness of the jobs. Dynasearch is more effective than traditional first-improve or best-improve descent in our computational tests. Furthermore, this superiority is much greater for starting solutions close to previous local minima. Computational results also show that an iterated dynasearch algorithm in which descents are performed a few random moves away from previous local minima is superior to other known local search procedures for the total weighted tardiness scheduling problem.
production scheduling: single machine, sequencing, analysis of algorithms, dynamic programming
0899-1499
52-67
Congram, Richard K.
606718f4-ff17-42c2-9172-57d7322cfab5
Potts, Chris N.
58c36fe5-3bcb-4320-a018-509844d4ccff
van de Velde, Steef L.
e6a2c648-1d3c-44b5-8b5b-d346edb09b2d
Congram, Richard K.
606718f4-ff17-42c2-9172-57d7322cfab5
Potts, Chris N.
58c36fe5-3bcb-4320-a018-509844d4ccff
van de Velde, Steef L.
e6a2c648-1d3c-44b5-8b5b-d346edb09b2d

Congram, Richard K., Potts, Chris N. and van de Velde, Steef L. (2002) An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem. INFORMS Journal on Computing, 14 (1), 52-67. (doi:10.1287/ijoc.14.1.52.7712).

Record type: Article

Abstract

This paper introduces a new neighborhood search technique, called dynasearch, that uses dynamic programming to search an exponential size neighborhood in polynomial time. While traditional local search algorithms make a single move at each iteration, dynasearch allows a series of moves to be performed. The aim is for the lookahead capabilities of dynasearch to prevent the search from being attracted to poor local optima.
We evaluate dynasearch by applying it to the problem of scheduling jobs on a single machine to minimize the total weighted tardiness of the jobs. Dynasearch is more effective than traditional first-improve or best-improve descent in our computational tests. Furthermore, this superiority is much greater for starting solutions close to previous local minima. Computational results also show that an iterated dynasearch algorithm in which descents are performed a few random moves away from previous local minima is superior to other known local search procedures for the total weighted tardiness scheduling problem.

Full text not available from this repository.

More information

Published date: 15 January 2002
Keywords: production scheduling: single machine, sequencing, analysis of algorithms, dynamic programming
Organisations: Operational Research

Identifiers

Local EPrints ID: 29622
URI: http://eprints.soton.ac.uk/id/eprint/29622
ISSN: 0899-1499
PURE UUID: ff32a6aa-0c88-42fd-a5c3-15bab7b18171

Catalogue record

Date deposited: 11 May 2006
Last modified: 22 Jul 2020 16:51

Export record

Altmetrics

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.

×