Assembly Line Balancing Problems Solved by Estimation of Distribution

In this paper, we propose an new algorithm based on an estimation of distribution (ED) to solve the type II assembly line balancing problem (ALBP-II). This problem aims to assign a set of assembly operations subject to precedence constraints to a given number of workstations of an assembly line in o...

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Bibliographic Details
Published in2007 IEEE International Conference on Automation Science and Engineering pp. 123 - 127
Main Authors Liya Gu, Hennequin, S., Sava, A., Xiaolan Xie
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2007
Subjects
Automation
Computational modeling
Costs
Face
Genetic algorithms
Production
Robotic assembly
Simulated annealing
Stochastic processes
Workstations
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ISBN9781424411535
142441153X
ISSN2161-8070
DOI10.1109/COASE.2007.4341810

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Summary:In this paper, we propose an new algorithm based on an estimation of distribution (ED) to solve the type II assembly line balancing problem (ALBP-II). This problem aims to assign a set of assembly operations subject to precedence constraints to a given number of workstations of an assembly line in order to minimize the cycle time. We prove that the optimal solution for determinist ALBP-II problem can maximize the reliability of the least reliable station in the line if the operation times are random and normally distributed with constant variance-to-mean ratio. The ED algorithm is a population-based algorithm. The simulation results show that ED algorithm outperforms the simulated annealing algorithm especially for large-scaled problems.
ISBN:9781424411535
142441153X
ISSN:2161-8070
DOI:10.1109/COASE.2007.4341810