2016
MAS 2016 Proceeding
Multi-objective evolutionary algorithms of correlated storage assignment strategy
Authors: Y. Zhang
Abstract
The traditional research on storage assignment strategies mostly concerns the single-objective optimisation problem (SOP) of travel distance in order- picking systems, in spite of diverse criteria. Considering the correlation between stock-keeping units, this paper presents multi-objective evolutionary algorithms of correlated storage assignment strategy for the multi- objective optimisation problems (MOP). Two types of objectives are considered. One is time consumption, consisting of travel time (converted from travel distance) and pick time, implying the MOP into SOP. The other is a parallel convergence of time consumption and energy expenditure. The multi-objective insertion and exchange algorithms are developed, and further improved through a skip method. After that, a model for a single-block warehouse with four routing strategies is built in Matlab to evaluate these algorithms. The experiment shows that the correlated storage assignment strategy can improve multiple objectives, by comparing with the full-turnover strategy.
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