Reactive Search Optimization (RSO): Continuous Optimization
Contact us to buy or request information
A scenario for applying Reactive Search Optimization is where a system (an electronic system, a production plant, a fleet of trucks, a business process) requires you to set some operating parameters (knobs, switches, travel plans, procedures) to improve its function. Depending on how the parameters are set, the system is going to give a better or worse outcome (measured by production speed, net income, fuel consumption, customer satisfaction...), as shown by the following figure.
In order to optimize the outcome, a simple loop is performed: set the parameters, observe the outcome, then change the parameters in a strategic and intelligent manner until a suitable solution is identified.
The intelligence of the process lies in the Reactive Search Optimization component, which decides about the next step to take based on information collected during the ongoing exploration of alter natives. In order to operate efficiently, Reactive Search Optimization uses memory and intelligence, to recognize ways to improve solutions in a directed and focussed manner.
The RSO tool in LIONsolver 2.0 provides a simple way for the user to solve problems with continuous parameters (floating-point numbers). The user defines the system to be optimized and invokes a powerful RSO solver that aims at locating the best values for the operating parameters.
