Research On The Multi-objective Optimization And Application Of Duration-cost-quality Of Project Based On The Multiple Ant Colony Algorithm

In today’s increasingly competitive society, how to achieve the project’s multi-objectiveoptimization of short duration, low-cost and high-quality is an urgent problem for enterpriseto deal with. For the project, these three goals are directly related to the success of theproject as the key factors. In the other words, to complete a project, the enterprise must to beable to guarantee to be delivered in a short period of delivery, control costs making it to beprofitable, as well as ensure that project to achieve the required quality indicators whichcountry, the industry or the owners ordered. None of these three goals can be neglected.Therefore, how to achieve the comprehensive optimization of the duration, cost and qualityis a subject worthy of study in the field of project.The thesis based on the deep analysis of the status of the multi-objective optimization,states a detailed study working on the multi-objective optimization model and methods. Inthe normal condition, several sub-goals of the multi-objective optimization problem areconflicting. So that it is not like the single objective problem which can obtain the onlyoptimal solution, but find the Pareto Front as compromise solutions. Around Model buildingof the multi-objective optimization, this thesis fully take account of the complexity of theintrinsic relationship between the duration, cost, quality, and do not blindly assume therelationship as the linear or nonlinear function, but indicate it in accordance with itsscientific method. On the basis of the existing multi-objective optimization literature, in theprocess of building a quality model, by introducing the idea of the QFD method which iscommonly used in the product design stage, the method to determine the impact of activitieson the quality of the overall project is more scientific. Considering the problem oflarge-scale calculations in the actual project, the general method is difficult to solve.Therefore, the thesis propose an improved multiple colony ant algorithm in the basic of antcolony algorithm. In the algorithm, every sub-goal can be represented by an ant colony.While the three colonies find the optimal solution, they can coordinate mutually throughhybridization and mutation of the pheromone on the section, in order to find the Paretosolutions, which achievs the evolutionary innovation between colonies.In order to indicate the effectivity of the proposed model and algorithm, afterinvestigation in the Five-Dimensional Highway Survey and Design Institute, Jingzhou City,this thesis does the empirical research on the cable project of Jingxin line of Provincial Highway, Zhangjin Town, Qianjiang City. Through the project’s data processing andmulti-objective optimization applications, the thesis produces the optimized solution forproject to achieve short duration, low-cost and high-quality, and proposes improvableadvices to the existing project management problems.