Comprehensive Optimization For Three Multi-objective In Construction Based On GA

Duration, cost and quality is the three main objectives of the construction. The performance of these three objectives can directly affect the entire target of the project .The best solution for a project is to achieve high quality with low cost in a proper time limit. But the previous model which could only resolve the time-cost trade-off problems that cannot satisfy decision makers'requirement. Because of these three goals are conflicting, and if one of the goal is improvement, other goals will be weakened inevitably. So therefore we can only enable the overall goal of project to achieve superiorly , that is to say under the premise of the total target is satisfied, to ensure the quality is relatively high, relatively short duration and the cost is relatively low.As a result of the limitation of the method, and most of the optimal method is about two goals of the three objectives, so we should find a method which is contains three goals. In predecessor's research results, there are to types of synthesis optimization models: and one of the models is established on the base of the relation of time-cost, time-quality is linear relationship; and the other model is established on the base of the relation of time-cost, time-quality is unlinear relationship. And this paper proposed two synthesis optimization models which should be soluted by Genetic algorithm is established on the base of these two types of relation. With this method you can obtain some solutions, and the policy-maker can choose one of it which is satisfied himself. And these two methods will be compared with each other, and the way of how to choose will be pointed out.Simultaneously in order to avoid the inputs of resource is overised in unit of time ,we proposed a two stage optimization model ,the first stage established a synthesis optimization models which is based on the relationship of the time, the quality and the cost is the misalignment, and it uses chromosomes which building up by mode to carry on the heredity operation; The second stage is to choose a non-poor solution which obtains from the Decision-maker from the first stage inputs to this stage to carries on the resource leveling optimization, it take the time in resources variance minimum as the objective function, takes the gene value which is non-critical process's beginning time to make up of the chromosome to carry on the heredity operation, An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating and visualizing optimal tradeoffs among construction time, cost and quality, and resource.