Title: Assumptions for inventory modelling: insights from practice

Authors: Lauri Lättilä; Samuli Kortelainen; Per Hilletofth

Addresses: SimAnalytics Oy, Kaisaniemenkatu 3 A 8, FI-00100, Helsinki, Finland ' SimAnalytics Oy, Kaisaniemenkatu 3 A 8, FI-00100, Helsinki, Finland; Department of Industrial Engineering and Management, LUT School of Business and Management, Lappeenranta University of Technology, P.O. Box 20, FI-53851, Lappeenranta, Finland ' Department of Industrial Engineering and Management, School of Engineering, Jönköping University, P.O. Box 1026, SE-551 11, Jönköping, Sweden; Department of Industrial Engineering and Management, University of Gävle, SE-801 76, Gävle, Sweden

Abstract: Many types of models have been developed to analyse multi-echelon supply chains. These models tend to rely on certain assumptions which might be too restrictive to be used in practical applications. In this paper we present a decision support system developed for a manufacturing company to aid decision making in both manufacturing and distribution strategy. The model is based on the assumptions of the decision-makers instead of relying on a pre-existing model architecture, which guarantees that the assumptions made are not too restrictive for practical use. The decision support system is based on agent-based modelling. The model was done in close co-operation with the personnel from the case company, and emphasis was based on how the company can use the model in decision making without requiring any special expertise in developing the supply chain alternatives. By using agent-based modelling we were able to take the central assumptions into account and create a decision support system, which the supply chain manager can use to evaluate various supply chain alternatives.

Keywords: inventory management; inventory modelling; simulation; decision support.

DOI: 10.1504/WRITR.2019.099135

World Review of Intermodal Transportation Research, 2019 Vol.8 No.2, pp.147 - 166

Received: 06 Mar 2018
Accepted: 13 May 2018
Published online: 16 Apr 2019 *

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