Simulation demos

Contents:

Download demos
Metrics obtained
From Theory to Reality
Why OpenSIMPLY?

The OpenSIMPLY demo models contain the queuing theory examples representing call centers of varying complexity. Call center simulation modeling is an important approach in the scientific research of call centers. All these examples are useful for both learning and practice.

A new version of OpenSIMPLY Demos has been released. It contains many improvements in functionality, the use of COMTAY 5.0 as an engine, as well as support for the resolutions of modern displays.

The models are compiled for 32-bit and 64-bit platforms for Windows and Linux and packed in the corresponding archives.

Download demos

The latest stable release is OpenSIMPLY Demos 4.3 Download demos

The OpenSIMPLY simulation demo is free software; you can use it or redistribute under the terms of the End-User License Agreement.

Installation

The OpenSIMPLY demos are the simulation models already compiled into executable binaries.

No installation required, even the OpenSIMPLY.

The package only needs to be unpacked to the preferred location and the desired model just needs to be run as an executable.

Uninstall demos

Remove the directory with unpacked demo files. No other actions required.

Metrics obtained

When simulating the demo models, important call center metrics are obtained:

Average Speed of Answer (ASA)
Average Handle Time (AHT)
Average Waiting Time (AWT)
Average Call Abandonment Rate (ACAR)
Agent Utilization
Call Arrival Rate
Percentage of Calls Blocked
Lost Calls Rate

The demos provide standard and extended statistics for simulation models of call centers too.

Feel free to ask a question or report an issue.

From Theory to Reality: Call Center Evolution in OpenSIMPLY

This series of demo models demonstrates how OpenSIMPLY bridges the gap between abstract queuing theory and simulation of real-world business processes.

The Ideal Model (M/M/c Queue)

The first model represents a classic mathematical abstraction.

Concept: Customers have infinite patience, and system resources (queue capacity) are unlimited.

Implementation: Built using basic Generator, Queue, and Selector blocks.

Goal: Establishing a baseline for performance metrics under "perfect" conditions.

The Constrained Model (M/M/c/K Queue with Reneging)

The second model introduces real-world physical and psychological constraints.

Concept: The queue has a limited capacity, and customers may "lose patience" (reneging) and abandon the call if the wait is too long.

Implementation: The Queue block is configured with finite capacity and a timeout. In this model, timed-out entities are simply counted as lost.

Goal: Analyzing service level and abandonment rates under resource pressure.

The Realistic Business Model (G/M/c/K Queue with Reneging and Retrials)

The final model captures the complex feedback loops of human behavior.

Concept: Abandoned customers don't just disappear; a portion of them will attempt a "retrial" after a certain delay.

Implementation: The advanced YQueue block is used to redirect impatient entities through an Infinite Server block (simulating "think time" before a redial) and back into the system via a Mixer.

Goal: Studying how retrials impact the arrival process (turning it into a Non-Poisson process) and calculating the true load on agents.

Why OpenSIMPLY?

These demo models cannot cover all the specter of OpenSIMPLY abilities. Beyond these examples, the framework supports:

Complex Routing: Advanced decision-making using custom selection logic.
Resource Management: Detailed modeling of agent shifts, breaks, and skill-based routing.
Statistical Depth: Extensive data collection for custom distributions and bottleneck analysis.
Integration: The ability to embed simulation logic directly into larger Delphi/Pascal applications.

The transition from a standard Queue to the YQueue block allows researchers to do more than just log losses. It enables the simulation of complex routing for abandoned entities—whether they are redirected to a callback service, an IVR, or a retrial loop—making OpenSIMPLY a powerful tool for authentic system optimization.