Papers

Saving and Restoring Anylogic 6 Model Snapshot


We are pleased to announce a new feature available in AnyLogic 6 Professional Edition: now you are able to save the full state of a model (the snapshot) during runtime to a file, restore it at a later time and continue running simulation from the same point. This feature may be useful in several cases:

  • Resilience: when a simulation takes very long time to complete, it may make sense to save its state periodically so that you do not have to start everything...

A multi-structural framework for adaptive supply chain planning


A trend in up-to-date developments in supply chain management (SCM) is to make supply chains more agile, flexible, and responsive. In supply chains, different structures (functional, organizational, informational, financial etc.) are (re)formed. These structures interrelate with each other and change in dynamics. The paper introduces a new conceptual framework for multistructural planning and operations of adaptive supply chains with structure dynamics considerations. We elaborate a vision of...

Supply chain multi-structural (re)-design


In the framework of supply chain (re)- design (SCD), different structures (functional, organizational, informational, etc.) are (re)- formed. These structures are interrelated and change in their dynamics. How is it possible to avoid structural incoherency and consistency and to achieve comprehensiveness by (re)- designing supply chains? This paper introduces a new approach to simultaneous multi-structural SCD with structure dynamics considerations. We elaborate a new conceptual model and...

The aero-engine value chain under future business environments


Abstract Agent-based modelling is gaining popularity  for investigating the behaviour of complex systems involving interactions of many players or agents. In this paper an agent-based simulation modelling technique is applied to understand the long term implications of strategy decisions for an aerospace value chain. The industry has unique elements including new business models, high levels of collaboration, long product lifecycles and long periods before positive paybacks are...

Using AnyLogic and agent-based approach to model consumer market


During the last decade numerous developments have resulted in significant methodological progress in consumer market modeling. While traditional statistical and equation-based methods continue to be useful, new approaches, such as Agent Based Modeling (ABM) successfully address their well known limitations, e.g. the necessity of “perfect mix” assumption for aggregated categories of consumers . In the highly dynamic, competitive and complex market environments (telecom, insurance...

A hybrid simulation optimization approach for supply chains


The main idea of our approach is to combine discrete-event simulation and exact optimization for supply chain network models. Simulation models are constructed in order to mimic a real system including all necessary stochastic and nonlinear elements. Such simulation models are used as proving grounds for analyzing and improving a real situation on a trial-and-error basis. A traditional optimization method on top of a simulation model has major disadvantages: The optimization method uses the...

Fully agent based modellings of epidemic spread using AnyLogic


The problem that we are going to conquer subsequently is a slight modification of the ARGESIM Comparison 17. This comparison does ask for the simulation of a SIR-type epidemic by means of lattice gas cellular automata (LGCA). At the end of this paper we will compare the outcome of such an approach with our ABS-result. The task is to model a SIR-type epidemic, an epidemic simplified in several ways. For example we assume a constant population over the whole simulation, thus no births or deaths...

Heterogeneity and network structure in the dynamics of diffusion


Abstract When is it better to use agent-based (AB) models, and when should differential equation (DE) models be used? Whereas DE models assume homogeneity and perfect mixing within compartments, AB models can capture heterogeneity across individuals and in the network of interactions among them. AB models relax aggregation assumptions, but entail computational and cognitive costs that may limit sensitivity analysis and model scope. Because resources are limited, the costs and benefits of...

How to build a combined agent based / system dynamics model in AnyLogic


  AnyLogic allows you to build a simulation model using multiple methods: System Dynamics, Agent Based and Discrete Event (Process‐centric) modeling. Moreover, you can combine different methods in one model: put agents into an environment whose dynamics is defined in SD style, use process diagrams or SD to define internals of agents, etc, etc. Any kind of mixed architecture is possible due to flexible object‐oriented AnyLogic modeling language. The choice of model architecture (how to partition...

Understanding retail productivity by simulating management practices


Abstract The retail sector has been identified as one of the biggest contributors to the productivity gap that persists between the UK, Europe and the USA. It is well documented that measures of UK retail productivity rank lower than those of countries with comparably developed economies. Intuitively, it seems likely that management practices are linked to a company’s productivity and performance. Significant research has been done to investigate the productivity gap and identify...