Abstract
Sensitivity analysis of selected parameters in simulation models of logistics facilities is one of the key aspects in functioning of self-conscious and efficient management. In order to develop simulation models adequate of real logistics facilities’ processes, it is important to input actual data connected to material flows on entry to models, whereas most models assume unified load units as default. To provide such data, pseudorandom number generators (PRNGs) are used. The original generator described in the paper was employed in order to generate picking lists for order picking process (OPP). This ensures building a hypothetical, yet close to reality process in terms of unpredictable customers’ orders. Models with applied PRNGs ensure more detailed and more understandable representation of OPPs in comparison to analytical models. Therefore, the author’s motivation was to present the original model as a tool for enterprises’ managers who might control OPP, devices and means of transport employed therein. The outcomes and implications of the contribution are connected to presentation of selected possibilities in OPP analyses, which might be developed and solved within the model. The presented model has some limitations. One of them is assumption that one mean of transport per one aisle is taken into consideration. Another limitation is the indirectly randomization of certain model’s parameters.
Highlights
The introduction of the paper consists of three interrelated parts
An order picking process is considered as one of the most important research interests in the field of internal logistics. This is due to the fact that an order picking process engages most of the resources of all processes taken in logistics facilities, as confirmed in Alicke et al (2001) and Ulbrich et al
pseudorandom number generators (PRNGs) is used to give a stochastic character to the processes that are reflected in the form of a simulation model for analyses of the order picking process in a high-bay warehouse
Summary
The introduction of the paper consists of three interrelated parts. The significance of the order picking process was described. Prior research on the order picking process was identified. Comprehensive discussion on the use of simulation approach for order picking is provided and objectives of the paper are defined
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