Skip to main content

Research Repository

Advanced Search

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

Staggemeier, Andrea; Clark, Alistair; Aickelin, Uwe; Smith, Jim

Authors

Andrea Staggemeier

Alistair Clark

Uwe Aickelin

Jim Smith



Abstract

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.

Citation

Staggemeier, A., Clark, A., Aickelin, U., & Smith, J. A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem

Conference Name 16th Triennial Conference of the International Federation of Operational Research Societies (IFORS 2002)
Deposit Date Oct 22, 2007
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/605
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf

Files


02ifors_andrea.pdf (64 Kb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





You might also like



Downloadable Citations