DocumentCode :
2452627
Title :
Biologically inspired genetic algorithm to minimize idle time of the assembly line balancing
Author :
Razali, Noraini Mohd ; Geraghty, John
Author_Institution :
Sch. of Mech. & Manuf. Eng., Dublin City Univ., Dublin, Ireland
fYear :
2011
fDate :
19-21 Oct. 2011
Firstpage :
105
Lastpage :
110
Abstract :
Assembly line balancing (ALB) is a well-known combinatorial optimization problem in production and operations management area. Due to the NP-hard nature of the ALB problem, many attempts have been made to solve the problem efficiently. In this study, biologically inspired evolutionary computing tool which is genetic algorithm (GA) is adopted to solve the ALB problem with the objective of minimizing the idle time in the workstation. The key issue in solving ALB is how to generate a feasible task sequence which does not violate the precedence constraints. This task sequencing is a vital work to be solved prior assigning tasks to workstation. In order to generate only feasible solution, a repairing strategy based topological sort is included in the GA procedure. The ALB test problems benchmarked from the literature are used in the study and the computational results show that the proposed approach is capable to obtain feasible solution with minimum idle time for a simple model assembly line.
Keywords :
assembling; combinatorial mathematics; genetic algorithms; maintenance engineering; minimisation; production management; ALB problem; NP-hard problem; assembly line balancing; biologically inspired genetic algorithm; combinatorial optimization problem; evolutionary computing; idle time minimisation; operations management; production management; repairing strategy; task sequence; Assembly; Biological cells; Genetic algorithms; Genetics; Optimization; Workstations; assembly line balancing; genetic algorithm; idle time; task sequencing; topological sort;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on
Conference_Location :
Salamanca
Print_ISBN :
978-1-4577-1122-0
Type :
conf
DOI :
10.1109/NaBIC.2011.6089425
Filename :
6089425
Link To Document :
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