OptQuest

OptQuest is an integration that can be added to an existing Simul8 license, allowing you to incorporate optimization within your simulation models. You can access it under the Advanced tab. Please note, OptQuest is not available if you are on a monthly subscription.

Optimization consists of different techniques to allow you to find the optimal solution to a problem. To setup an optimization problem, you will need an objective (or multiple objectives) and decision variables which are the variables you want to change to achieve your objective(s). To further the complexity of your optimization problem, you can also add constraints to your decision variables.

Simulation allows you to carry out what-if analysis to explore a wide range of options, while optimization’s purpose is to provide “what’s best” analysis to determine the optimal solution for a problem. Although these objectives are significantly different, combining these approaches makes it possible to maximize their benefits and aid your decision-making.

When using simulation, you can model more complex situations and scenarios where optimization would be less effective on its own. As you go through the exploratory process of building the simulation, you start to get an understanding of factors that impact your model. With this knowledge, you can use optimization more effectively as you already have a full understanding of the process and potential significant factors.

Using optimization removes inaccuracies inherent to trial-and-error methods, also allowing you to save time in finding the best solution to a given problem. Further, when there are many (often competing) decision variables to consider, OptQuest will allow you to quickly identify which parameters you need to use in order to reach the optimal solution.

OptQuest runs Simul8 Trials and makes changes within the parameters that you set. Its purpose in this is to improve on the result achieved from the previous Simul8 Trial. In OptQuest, you specify certain parameters (that must be listed on the KPI Summary) that will be changed from trial to trial that the optimization will be conducted on.

There are many uses cases for OptQuest. Some of them include:

• Optimizing manufacturing process design
• Optimizing performance metrics (i.e., throughput, patients seen, documents processed, etc.)
• Optimizing supply chain operations (i.e., improving reliability)
• Optimizing utilization and management of patient flow in operating rooms and emergency departments to reduce waiting times

OptQuest uses several techniques including metaheuristics optimization, tabu search, scatter search, integer programming, and neural networks.

Check out our step-by-step tutorial for guidance on running an optimization model in Simul8.

Interested in using OptQuest? Contact our team of simulation advisers to discuss your needs.

• OptQuest Tutorial
• KPI Summary
• Making your own results