Dynamic multi-project selection planning with inheritance-constraints and its immune genetic optimization

This work investigates a hybrid optimization model of resource-constrained dynamical multi-project selection planning and its immune genetic algorithm. The model is designed based oil the dynamical characteristic of multi-project selection planning and the limits of inheritance and resource. Further, a dynamical bi-level programming decision model is developed, relying upon term-subpopulations, topological sorting and the relations of inheritance and time precedence among terms. Thereafter, an immune genetic algorithm associated to the structure of the basic genetic algorithm and the characteristics of diversity, memory and so forth in the immune system is proposed to solve the high-dimensional bi-level programming model. Finally, experimental results and comparison show the rationality of the model and the effectiveness of the algorithm proposed.