Multi-objective Optimization Of Engineering Project Based On Hybrid Particle Swarm Optimization

With more attention paid on the efficiency of engineering project execution and thedevelopment of the multi-objective optimization technology, Multi-objectiveOptimization of Engineering Project has become an important research topic.Most of the researches on multi-objective optimization of engineering project beforefocused on the project schedule-direct cost relationship, then used the traditionalmathematic method to optimize the two-goal optimization model. Very few of theresearches before included the goal of the project quality, besides, the traditionalmathematic optimization method has complicated operations and many requirementsto the optimization model.Using the means of contrasting analysis and instance validation, the thesis utilizeshybrid particle swarm optimization method to optimize the multi-objective of theengineering project. The result of this research not only enriches the academicknowledge of multi-objective optimization of engineering project but also provide aneffective optimization technology.Firstly, the thesis analysis the relationship between project schedule and cost;schedule and quality; cost and quality qualitatively, then set up the quantitative modelamong the threes goals. The origination of the particle swarm optimization (PSO)and the improved algorithm of PSO are also introduced in this thesis. Since thetradition mathematic method for the multi-objective problems has such disadvantageslike complicated operations and easy to get into the local best, this thesis borrows theidea of Crossover and variation operation from the genetic algorithm to improve theperformance of PSO, forming a new algorithm—hybrid particle swarm optimization(HPSO). At the end of this thesis, the new algorithm is used in a real example, andthe result shows the HPSO has standout efficiency and practicability in dealing withthe multi-objective problems.