A Simulation Study of Logistics Activities in Mixed-model Assembly Lines with Genetic Algorithm

Abstract

Logistics activities in mixed-model assembly lines involve the material flow that depends heavily on the arrival sequence of products to be assembled in these lines. The main effort of this paper is to analyse how the arrival sequence of mixed models to a specific assembly line affects the logistics activities of the line, where a smoothly- and evenly- distributed material flow is desired. However, the uncertainty caused by the stochastic arrival sequence of customer orders in a make-to-order environment increases the complexity of logistics activities. Confronted with this uncertainty and complexity, we put the logistics activities into a more vivid and intuitive scenario by simulating the behaviour of materials. To begin with, the logistics activities occurring in a specific automobile assembly line is investigated. Secondly, a logistics simulation model of the assembly lines is built. Using the genetic algorithm toolbox embedded in Matlab7.0 package, we obtain subsequently an optimised model sequence that enables an evenly- distributed material flow. Finally, simulation results generated from Matlab7.0 Package are discussed.