Projects’ Multi-objective Optimization Studies Based On IGPSO

With the Reform and Opening up moving forward, Project are more and more Large-scale, complex, systematic, Target dimension are expanding. New problems,new goals, new requirements, new standards continue to emerge, to meet the needs of economic and social development. Past project management concepts and management techniques behind the economic and social development, This requires constantly sum up experience of their predecessors, research the new questions, using new methods, new theories study on the project multi-objective optimization.This paper summarizes and inheritances the research results of the predecessors in study of multi-objective optimization project make use of the intelligent algorithms taken achievements In recent years, to research new problems of Engineering management. By analyzing the advantages and disadvantages of Particle swarm intelligence algorithm, immune intelligent algorithm, genetic algorithm intelligent,and Build Immune Genetic Particle Swarm Optimization intelligence algorithm(IGPSO) model. Summarizing and learning from the predecessors’ experience and achievements mated ??in the field of engineering management, and Based on the relationship between time and cost, value engineering theory, hybrid system reliability theory, integrated project management theory, construction environmental assessment theories, build "Schedule- Quality- Cost- Safety- Environment" multi-objective optimization model. In the second half of the paper, use a Specific example to test"algorithm theory" and "multi-objective optimization model project.” I hope by the new theory, the use of new methods can have implications for future research.Meanwhile, the test results from the point of view of this paper the research of IGPSO and multi-objective optimization project had achieved the desired effect.