Agent Based Simulation Modeling

The Power of Complex Systems Modeling and Analysis: Cutting-Edge Agent-Based Simulation Services

Agent-based modeling is a cutting-edge computational approach used to model and analyze the behavior of complex systems. By simulating the actions and interactions of individual agents, simulation modeling allows organizations to study how these agents behave as a group and how they affect the overall system.

Whether you're looking to optimize your supply chain, study material flow and workcells, or design a new production line, our team of experts can help you harness the power of agent-based simulation to gain valuable insights and make informed decisions.

Request a Quote

PMI Agent Based Simulation Advantages & Benefits

30+ Years of Simulation Modeling experience, giving us the knowledge and capability to meet your exact requirements and provide expert insight
Custom Simulation solutions to meet your specific requirements
Customize your model to assist in “what-if” scenarios and planning
Provide insights to increase ROI, optimize pedestrian and traffic flow, and production lines.
Leverage a variety of advanced software and technology to meet your needs

Agent-Based Simulation Application Possibilities

Engineering:

Agent-based simulations are used to model and test complex systems and design new products, services, and systems. For example, an engineer can use an agent-based simulation to model the behavior of an autonomous vehicle in a traffic system, analyze the performance of a communication network, or optimize the operation of a power grid.

Business Applications:

In business, agent-based simulations can analyze and optimize supply chain systems, customer behavior, and marketing strategies. For example, a company can use an agent-based simulation to model the behavior of consumers in a market, analyze the impact of a new product launch, or optimize pricing strategies.

Urban Planning:

Urban planners can use agent-based simulations to study individual and group behavior in cities and inform planning decisions on land use, transportation, and more. They can model behavior, analyze the effects of projects, and support transportation planning.

Natural Resource Management:

Natural resource managers use agent-based simulations to study the impact of human activities on the environment and make informed decisions for sustainable resource use. These simulations can model the behavior of individuals, analyze the effects of practices, and support conservation efforts.

Optimize Systems with Agent Based Simulation Modeling

Graphical representation of pedestrian model

Infrastructure Design Optimization

Test layouts to determine their performance at different levels of capacity. Pedestrian simulation can highlight bottlenecks and areas seeing the most foot traffic with heatmaps and other data visualizations. These can help inform design alterations which can then be tested and compared through simulation.

Service Level Optimization

Simulate queues of patrons at concert venues, sporting events, airports etc. to identify the optimal number and placement of installations such as ticketing kiosks and security checkpoints to achieve a desired level of service.

Emergency Preparedness

Model evacuation and/or shelter-in-place plans in the event of an emergency. Using simulation, our team can determine the time to evacuate from any given setting, identify bottlenecks, and help with the planning of evacuation routes, and the placement emergency exits and personnel.

Industries that Benefit from Agent Based Simulation

Supply Chain Management

Manufacturing

Transportation & Logistics

Retail

Emergency Response

Utilities and Energy

Research and Development

Aerospace

Food and beverage

Architecture

Manufacturing Process Systems

Ecological Systems

Computer Science Systems

Social Systems

Economic Systems

Entertainment Venues

Event planning

Urban planning

Disaster response

Airports

Our Experts

With over 30 years of experience with simulation technology and software, PMI brings knowledge and experience to your project. We employ highly experienced team members who possess a wealth of knowledge in multiple industries. Let our qualified specialists help meet your needs!

Software & Technologies

Related Service: Industrial Engineering with Simulation Services

Two Engineers discussing on Industrial Engineering

In industrial engineering, simulation is used to analyze and evaluate spaces in terms of performance, dimensions, throughput times, capacities, staffing requirements, and other planning parameters. The visual representation capabilities of simulation also make it possible to compare different scenarios for a space and evaluate their effectiveness.

PMI offers simulation services to a wide range of clients, including warehouses, manufacturing plants, and automotive companies. The ability to test processes and explore "what-if" scenarios before implementation can help prevent costly mistakes and aid in making informed decisions.

Industrial Engineering with Simulation Services

Frequently Asked Questions in Agent Based Simulation Services

What is Agent-Based Modeling and Simulation?

Agent-based simulation modeling is a way of studying how groups of autonomous agents behave and interact. These agents are created and placed in a virtual environment where they follow set rules and interact with each other and their surroundings. By observing their behavior over time through simulation, we can gain insights into how the group as a whole functions and the impact they have on the system.

What is the process for an Agent-Based Simulation Project?

Agent-based simulation work typically involves the following steps: Problem definition and analysis: The first step is to clearly define the problem that needs to be solved and analyze the data and information related to the problem. Model design: The next step is to design the simulation model, which involves creating a virtual environment and defining the rules and behavior of the agents. This may include defining the agents' characteristics, decision-making processes, and interactions with one another and the environment. Parameter estimation and validation: Once the model has been designed, the parameters of the model must be estimated and validated using data and expert knowledge. This ensures that the model accurately represents the real-world scenario being studied. Simulation run: The simulation is then run and the behavior of the agents is observed over time. This allows the analyst to study the interactions between the agents and the system as a whole. Results analysis: The final step is to analyze the results of the simulation and draw conclusions about the behavior of the system being studied. This may involve visualizing the results and comparing the simulated outcomes to real-world data. Model refinement and iteration: Based on the results, the model may need to be refined or adjusted, and the simulation process may need to be repeated several times to get the desired results. Final report and presentation: The final results are presented in a comprehensive report that summarizes the findings and provides recommendations based on the results of the simulation.

How are environments and obstacles put into agent-based simulation software?

Environments can be imported as CAD or BIM files directly into the simulation environment. Additional obstacles can be built using included tools in the software.

Can you build a test environment without a preexisting 3D model?

Yes! Using the aforementioned tools in simulation software, an environment can be built from scratch. Pedestrian simulation software images such as maps to aid in the building of an environment.

Can pedestrian simulations include other flows like vehicle traffic?

When studying pedestrian flows in outdoor environments such as town centers, a major factor impacting the movement of pedestrians is the presence of automobiles and other forms of transport. As a result, every pedestrian simulation software we use can include cars, trams, buses, etc. with true-to-life traffic signaling and driver behavior.