GA's Arithmetic On Time-Cost Optimization In Architecture Engineering

The time-cost optimization is one of the most crucial aspects of construction project planning, it belong to multi-objective optimization problem. Multi - objective optimization is a difficult problem and a research focus in the fields of engineering. Classical Multi-objective optimization methods have several shortcomings in solving high dimension and multi-model problems. Many problems which often depend on the mathematical characteristics of the objective functions can not be solved satisfactorily by the traditional approaches.In order to solve these problems.researchers have developed many multi-objective optimization genetic algorithms based on Simple Genetic Algorithm.and, as the capability of searching the global best solutions rapidly, Genetic Algorithm has become a research area with increasing importance.In this thesis, the basic concepts, theories and frames of the evolutionary algotithm and the multi-objective optimization are systematically introduced firstly. Explaining the concept of the paerto optimization solutions.To summarize some classical muti-objectives optimization methods and show the limits of them .In the paper, we also introduce the basic theory of genetic algorithm including its working flow and the common technology that has been used in the optimization process. at the same time to use multi-stage process planning (PPP) model and critical path method to solve the problem of multi-objective optimization and to find pareto values through using the GA method and evolution Strategy.An application example is analyzed to illustrate the use of the model and algorithm in optimization.proved the validity of the improved GA. finally tabled a mixed GA on Niched-Pareto and improved GA and proved the validity of this GA.