DocumentCode :
3153466
Title :
A hybrid Ant Colony System for machine assignment problem in flexible manufacturing systems
Author :
Deroussi, L. ; Fonseca, J. Barahona da
Author_Institution :
LIMOS, Univ. of Clermont-Fd, Clermont, France
fYear :
2009
fDate :
6-9 July 2009
Firstpage :
205
Lastpage :
210
Abstract :
This paper deals with a new problem: the conjoint solution of machine assignment, job scheduling and vehicle scheduling in an FMS environment. This problem arises when we wish to reconsider the design of an FMS by evaluating its functioning with a higher model granularity. The experimental results obtained show that, in many cases, a simple reorganization of the machines can improve the overall productivity of an FMS. The evaluation model considered permits to synchronize the handling material system with the production tools, in order to minimize the time required for the production of a given set of jobs (makespan). We propose a solution approach based on an hybridized ant colony system (ACS). ACS integrates the knowledge of the current design of the FMS for constructing new machine assignments. Their makespan is evaluated by a black box optimization subroutine.
Keywords :
automatic guided vehicles; flexible manufacturing systems; job shop scheduling; machine tools; materials handling; optimisation; FMS; automated guided vehicle scheduling; black box optimization subroutine; flexible manufacturing system; hybridized ant colony system; job scheduling; machine assignment problem; machine tool; material system handling; production tool; Algorithms; Ant colony optimization; Costs; Flexible manufacturing systems; Job production systems; Job shop scheduling; Processor scheduling; Production systems; Productivity; Vehicles; Ant Colony System; Flexible Manufacturing Systems; Hybrid Methods; Machine Assignment Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers & Industrial Engineering, 2009. CIE 2009. International Conference on
Conference_Location :
Troyes
Print_ISBN :
978-1-4244-4135-8
Electronic_ISBN :
978-1-4244-4136-5
Type :
conf
DOI :
10.1109/ICCIE.2009.5223781
Filename :
5223781
Link To Document :
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