PWR Fuel Management Optimization Using a New Integer Coded Genetic Algorithm

The objective of this paper is to develop a new genetic algorithm (GA) for designing the loading pattern (LP) for pressurized water reactors (PWR). Because of huge number of possible combinations for the fuel assemblies (FA's) loading in a core, finding the optimum solution is truly a complex problem. In common genetic algorithm the mutation and crossover techniques are used to optimize an objective function but in this paper a new modified crossover along a unique technique is presented. In this study flattening of power inside a reactor core is chosen as an objective function. To obtain optimal FA arrangement, a core reload package code, MAKGA, is developed. This code is applicable for all types of PWR core having different geometries and designs with an unlimited number of FA types. The result is well improved in comparison with pattern proposed by designer.