The majority of nuclear reactors are operated in cycles with periodic complicated and expensive refueling outages. The fuel in the reactor core is not homogeneously burned and usually, a third of the fuel assemblies are replaced during refueling. The loaded fresh fuel assemblies, together with the remaining depleted ones, are rearranged to form a new core configuration. The new core configuration should maximize the energy production until the subsequent refueling outage while still satisfying all safety limitations and operational constraints. For example, the core excess reactivity should be maximized to ensure a long cycle and high fuel burnup, while maintaining the ability to control and shutdown the reactor within the required safety margins. The problem of optimizing the core configuration is of great importance for electric utilities as well as for research reactors operating with limited nuclear fuel stockpile.

During the past two decades, the optimization problem of designing the best core configuration has been addressed by utilizing several approaches and methods. One of the more successful methods used is the so-called evolutionary algorithm, specifically the genetic algorithm.  This field of study is of true inter-disciplinary nature in the sense that a combination of expertise in both evolutionary algorithms and nuclear reactor physics is required.

In this talk, we will describe the unique features of nuclear core configuration design, demonstrate the usage and implementation of genetic algorithms for this optimization problem, and present our recent scientific contributions to this active field of research.