A Hybrid System Dynamics-Discrete Event Simulation Approach to Simulating the Manufacturing Enterprise

With the advances in the information and computing technologies, the ways the manufacturing enterprise systems are being managed are changing. More integration and adoption of the system perspective push further towards a more flattened enterprise. This, in addition to the varying levels of aggregation and details and the presence of the continuous and discrete types of behavior, created serious challenges for the use of the existing simulation tools for simulating the modern manufacturing enterprise system. The commonly used discrete event simulation (DES) techniques face difficulties in modeling such integrated systems due to increased model complexity, the lack of data at the aggregate management levels, and the unsuitability of DES to model the financial sectors of the enterprise. System dynamics (SD) has been effective in providing the needs of top management levels but unsuccessful in offering the needed granularity at the detailed operational levels of the manufacturing system. On the other hand the existing hybrid continuous-discrete tools are based on certain assumptions that do not fit the requirements of the common decision making situations in the business systems.

Argus Invasive Species Spread Model Constructed Using Agent-based Modeling Approach and Cellular Automata

The stochastic Argus Invasive Species Spread Model (AISSM) is constructed using an Agent-Based Modeling (ABM) approach with cellular automata (CA) to account for spatial relationships and changes in those relationships over time. The model was constructed to support a wide range of geographical locations; however, this paper focuses on its application in the state of California. A timeseries of daily historical weather observations on a 6- kilometer grid was obtained for six weather variables important to insect and disease development. Weather conditions were then simulated using the K- nearest neighbor (K-nn) regional weather generator. The weather simulations were summarized into a monthly time-step and coupled with satellite land cover imagery to identify a habitat quality for each simulated month. This information was combined with the introduction of invasive species in the AnyLogic™ modeling environment. The spread of invasive species is driven by the habitat quality layer, which regulates its dispersal rate.

A Simulation-Based Investigation of Freight Transportation Policy Planning and Supply Chains

Regional freight transportation policy planning is a difficult task, as few policy-planners have adequate tools to aid their understanding of how various policy formulations affect this complex, socio-technical system. In this paper, we develop a proof-of-concept model to simulate the impacts of public policies on freight transportation in a simulated region. We use the techniques of multi-disciplinary system design and optimization to analyze the formulation of regional freight transportation policies and examine the relative effects of policies and exogenous forces on the region in order to provide insight into the policy-planning process. Both single objective and multi-objective analysis is performed to provide policy-planners with a clear understanding of the trade-offs made in policy formulation.

An Object-oriented Process Flow Approach to ARGESIM Comparisons "Flexible Assembly System" with AnyLogic

Simulator: AnyLogic is an object-orientated, general-purpose simulator for discrete, continuous and hybrid applications. It supports modelling with UML – RT and the underlying modelling technology is based on Java. Since Version 4.5 AnyLogic provides different advanced libraries as the Enterprise Library which implements often used discrete model object classes like sources, conveyors, and sinks.  Model: As the Comparison addresses the possibility to define and combine submodels, the objectoriented approach of AnyLogic, using the Enterprise Library, seems natural. The model consists of eight stations connected by some conveyors (all predefined in the Enterprise Library). 

An Object-oriented Numerical Solution to ARGESIM Comparison “SCARA Robot” using AnyLogic

Simulator: AnyLogic is able to handle continuous, discrete and hybrid models. It is based on JAVA and therefore object-oriented. It offers drag-and-drop dialogues for the basic parts of the model’s structure as well as for animation. Everything needed is created as an instance of the ActiveObject class, starting with the ‘root’ class which represents the model to state variables (the ‘important’ variables which can appear on the left-hand side of an ODE and can be plotted), statecharts and animation.

An Object-oriented Hybrid Approach to ARGESIM Comparison "Crane and Embedded Control" with AnyLogic

Simulator: AnyLogic is a general-purpose simulation environment for discrete, continuous and hybrid systems. It employs UML-RT structure diagrams for building hierarchical models in object-oriented way and hybrid statecharts for behaviour specification. The generated model is Java and can be extended with user’s Java code. The simulation engine handles discrete events and dynamically changing sets of algebraic-differential equations. It automatically detects “change” (or “state”) events. Debugging and visualization facilities are present.

Coordination of production and ordering policies undercapacity disruption and product write-off risk: ananalytical study with real-data based simulations of a fastmoving consumer goods company

Performance impacts of ordering and production control policies in the presence of capacity disruptions are studied on the real-life example of a retail supply chain with product perishability considerations. Constraints on product perishability typically result in reductions in safety stock and increases in transportation frequency. Consideration of the production capacity disruption risks may lead to safety stock increases. This trade-off is approached with the help of a simulation model that is used to compare supply chain performance impacts with regard to coordinated and non-coordinated ordering and production control policies.

Supply Chain Management with Anylogic 4.0

Simulator: AnyLogic is a general- purpose simulator for discrete but also for continuous and hybrid applications. The modelling technology of AnyLogic is based on Java so that building simulation models using AnyLogic should be easy for experienced programmers. Model: According to the task of the comparison there are three Active Object Classes. The customer class corresponds to the wholesaler; the wholesaler class corresponds to the distributor class and to the factory class. In addition there is built a Message class that represents the movable goods as well as the orderings in the supply chain.

Distributed Simulation of Hybrid Systems with HLA Support

As engineers are confronted with designing increasingly complex systems composed of interconnected components of diverse nature, traditional methods of modeling and analysis become cumbersome and inefficient. In the paper we discuss one of the approaches to modeling and distributed simulation of hybrid (discrete/continuous) systems. We use hybrid state machines, where sets of algebraic-differential equations are assigned to states, to model complex interdependencies between discrete and continuous time behaviors. This framework is fully supported by UML-RT/Java tool AnyLogic developed at Experimental Object Technologies. We use High Level Architecture (HLA), a defacto standard for distributed simulation, as a communication and synchronization media for distributed hybrid simulation components. Integration of simulations developed with AnyLogic into HLA is considered.