An Ant Colony Optimization Approach for the Multi-Level Unconstrained Lot-Sizing Problem

Author

Homberger, J. ; Gehring, Hartmut

Author_Institution

Stuttgart Univ. of Appl. Sci., Stuttgart

fYear

2009

fDate

5-8 Jan. 2009

Firstpage

1

Lastpage

7

Abstract

An ant colony optimization approach for the multilevel unconstrained lot-sizing problem (MLULSP) is described and evaluated using 176 benchmark problems from the literature, with problem sizes varying from 5 to 500 products and up to 52 periods. The approach consists of a binary encoding of production plans. The lot-sizing decisions are mapped on a routing graph to apply the metaheuristic concept of ant systems. The proposed approach is competitive with the best known solution methods. It was possible with the new method to calculate new best solutions for 11 of the benchmark problems.

Keywords

binary codes; graph theory; lot sizing; materials requirements planning; optimisation; ant colony optimization approach; binary encoding; metaheuristic concept; multilevel unconstrained lot-sizing problem; production plan; routing graph; Ant colony optimization; Capacity planning; Encoding; Enterprise resource planning; Lot sizing; Materials requirements planning; Probability distribution; Production planning; Routing; Synthetic aperture sonar;

fLanguage

English

Publisher

ieee

Conference_Titel

System Sciences, 2009. HICSS '09. 42nd Hawaii International Conference on

Conference_Location

Big Island, HI

ISSN

1530-1605

Print_ISBN

978-0-7695-3450-3

Type

conf

DOI

10.1109/HICSS.2009.58

Filename

4755430