Practical Case Study of Norwegian Dairy Supply Chain Utilizing Multi-Method Approach
Explore a practical case study of the Norwegian dairy supply chain, employing a multi-method approach blending system dynamics and agent-based modeling. Discover the strengths and drawbacks of each approach, as well as the methodology and software used in the study.
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Presentation Transcript
Multi-Method Approach of System Dynamics And Agent-Based Modeling: A Practical Case Study of the Norwegian Dairy Supply Chain Takuma Ono | Supervisor: Hugo Herrera takuma.ono@gmail.com | Hugo.Herrera@uib.no 42nd International System Dynamics Conference Bergen, Norway August 7, 2024
Strengths of System Dynamics? (SD) Powerful tool for policy design Feedback systems theory Calculation based on series of integration equations Top-down modeling Drawbacks? Spatial information Heterogeneity
Values from Agent-Based (AB) Modeling? Computer simulation for individual behavior interactions within space Program process-based agent behavior Can display unplanned emergent behavior Bottom-up modeling Drawback? Model verification Long simulation times
Methodology Case Study Setting Consumer demand of dairy products in Norway Meeting demand with decreasing number of farms Case study focusing in Vestland Fylke 1,126 Dairy farms 5 Dairy Processors 43 kommuner (municipalities) The dairy supply chain is the setting for the methodology implementation, no policy recommendations
1. Independent agents are placed according to GIS coordinates 2. Agents acknowledge each other by distance and/or variables 3. The agents can make connections and exchange variables 4. Agents collectively produce milk to meet demand 5. Milk supply affects demand level ! Modeling Capability Reqs
Software Used Work done in AnyLogic 8 Java-based software with many useful off-the-shelf modules SD and AB simulation modules with familiar interface Agents are spatially positioned on integrated GIS map module Java programming ties the modules together into hybrid framework NOTE: Work is presented as a practitioner s experience as rather than formalized theoretical investigation This work is what/how, future studies should look at who/when/why
Causal Loop Diagram (CLD) SD-defined causality AB-defined causality
Hybrid Model Conceptualization Diagram 1. Supply agents placed onto GIS map 2. Agents seek supply chain partners using map distance 3. Agents have embodied SD structure for farm operation
GIS Component 1,126 dairy farm and 5 processor agents positioned with GIS 43 municipality polygon shapefiles Distance calculation with OpenStreetMap integrated in software Each farm and processors are independent decision-making agents GIS Map
Farm agents produce milk and send to partner Processor If finances are poor, they can decide to close If closing, farm agents can transfer herd to connected neighbor agent Agent Decision Process SD Module Component
Java Programming Required in Model Essential for agent behavior GIS map distance calculation Agent-agent interaction Transferring variables to appropriate model components Dynamically incorporating exogenous data source
Discussion & Conclusion AnyLogic was able to sufficiently implement the required hybrid modeling techniques in this case study SD brings calculation efficiency, clarity in narrative, rigorous modeling principles AB brings spatial/GIS, heterogeneity, interactive subnetwork SD-AB hybrid modeling is accessible, no longer require extensive coding skills, can be applied where desired Future work should look at formalized recommendation on when this methodology is best utilized
Thank You takuma.ono@gmail.com August 7, 2024
Background Literature Review SD-AB hybrid has been implemented in various approaches Purpose-built programming for the study (Duggan 2008) Customized modeling modules e.g. Repast (Geller & Alam 2010) Integrated, off-the-shelf solution e.g. NetLogo and AnyLogic (Choong & McKay 2014; Kieckh fer, 2014) AnyLogic 8 currently to be best one-stop-shop solution Java-based AB modeling, with familiar SD user interface
