A Modeling Framework for Supply Chain Simulation: Opportunities for Improved Decision Making*

Abstract

Owing to its inherent modeling flexibility, simulation is often regarded as the proper means for supporting decision making on supply chain design. The ultimate success of supply chain simulation, however, is determined by a combination of the analyst's skills, the chain members' involvement, and the modeling capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party's insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realizing the required overview and insight. Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualized, or form part of the time-indexed scheduling of events. In this article, we propose an alternative approach that explicitly addresses the modeling of control structures. First, we will conduct a literature survey with the aim of listing simulation model qualities essential for supporting successful decision making on supply chain design. Next, we use this insight to define an objectoriented modeling framework that facilitates supply chain simulation in a more realistic manner. This framework is meant to contribute to improved decision making in terms of recognizing and understanding opportunities for improved supply chain design. Finally, the use of the framework is illustrated by a case example concerning a supply chain for chilled salads.

A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

“…He furthermore suggests that it greatly affects the acceptability and credibility of simulation application results. Robinson (2008a, b) also considers the qualitative criteria by which to judge conceptual modelling and comes up with a set of four requirements based on criteria put forward by other modellers (Pritsker 1986;Henriksen 1988;Nance 1994;Willemain 1994;Brooks and Tobias 1996;van der Zee and van der Vorst, 2005). These are: validity, credibility, utility and feasibility (Robinson 2008a, b).…”

Conceptual modelling for simulation Part I: definition and requirements

“…Meanwhile, Brooks and Tobias (1996a) identify eleven performance criteria for a good model. Requirements are also briefly discussed by Pritsker (1986), Henriksen (1988), Nance (1994), and van der Zee and van der Vorst (2005). Outside of operational research there are some discussions, for instance, Teeuw and van den Berg (1997) who discuss the quality of conceptual models for business process reengineering.…”

The bullwhip effect in complex supply chains

“…In the field of supply chain management, one can use complex statistical methods and differential equations to manage simple supply chains, or use artificial intelligence (or agent based simulation) to achieve desired results. In many cases, simulation is a natural approach in studying supply chains as their complexity obstructs more traditional analytic evaluation [6][7][8], and agent based simulation is often geared towards the achievement of a system goal [9]. The choice of a modelling approach requires serious consideration of the needs of the project and the direction of the research to be undertaken.…”