Genetic algorithm with immigration strategy to solve the fixed charge transportation problem

This paper is about improving the performance of genetic algorithm (GA) to solve fixed-charge transportation problem (FCTP). Several approaches have been developed, based on adaptation and improvement operators. We propose a new adopting an immigration strategy maintain diversity in population then overcome stagnation values objective function. Thereby, we applied two types immigration, random memory-based immigration. The numerical results obtained with several standard instances FCTP demonstrate effectiveness these strategies GA. Especilly, for second strategy.