A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem

Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t....

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Main Authors: Staggemeier, Andrea, Clark, Alistair, Aickelin, Uwe, Smith, Jim
Format: Conference or Workshop Item
Published: 2002
Online Access:https://eprints.nottingham.ac.uk/605/
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author Staggemeier, Andrea
Clark, Alistair
Aickelin, Uwe
Smith, Jim
author_facet Staggemeier, Andrea
Clark, Alistair
Aickelin, Uwe
Smith, Jim
author_sort Staggemeier, Andrea
building Nottingham Research Data Repository
collection Online Access
description Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches.
first_indexed 2025-11-14T18:12:41Z
format Conference or Workshop Item
id nottingham-605
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T18:12:41Z
publishDate 2002
recordtype eprints
repository_type Digital Repository
spelling nottingham-6052020-05-04T20:32:28Z https://eprints.nottingham.ac.uk/605/ A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem Staggemeier, Andrea Clark, Alistair Aickelin, Uwe Smith, Jim Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches. 2002 Conference or Workshop Item PeerReviewed Staggemeier, Andrea, Clark, Alistair, Aickelin, Uwe and Smith, Jim (2002) A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem. In: 16th Triennial Conference of the International Federation of Operational Research Societies (IFORS 2002), Edinburgh, UK.
spellingShingle Staggemeier, Andrea
Clark, Alistair
Aickelin, Uwe
Smith, Jim
A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title_full A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title_fullStr A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title_full_unstemmed A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title_short A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem
title_sort hybrid genetic algorithm to solve a logt-sizing and scheduling problem
url https://eprints.nottingham.ac.uk/605/