A Research On Bidding Decision Of Green Construction Project Based On Rough Set Theory

Construction industry is one of the pillar industries to promote the rapid development of the national economy, at the same time, the booming construction industry consumes enormous resources and brings serious environmental damage. Currently, the idea of sustainable development has become a consensus of the entire human community who want to have a long-term development. In addition, the “green building”, which emphasizes the ideas that the buildings should adapt to the environment and the man and the nature should live in harmony, has become a highlight of the construction industry. In the entire life cycle of green building project, the construction phase is the key to ensure that the building can achieve the goal that the building should be “green”, so choosing the best construction unit by the way of bidding is inevitable. The bidding of construction units is usually based on the experience of the bidding for traditional construction project, and green construction project has a great difference with traditional construction project. It is necessary to find a more appropriate evaluation method for green construction projects.The paper regards the bid evaluation of green construction as the research object, introduces the basic knowledge of the green building and the bidding, uses the theory of attribute reduction in rough set, puts forward a bid evaluation model of green construction project based on rough set theory. In the bid evaluation model, firstly, we should establish the evaluation index system for green construction projects, considering a comprehensive and normative principles, secondly, by dealing with the value of qualitative and quantitative indicators in the index system of every bid document, we obtain unified dimensionless index property values that have been processed, thirdly, we should establish the new information system with the processed index values and determine the index weight using the attribute reduction and other related knowledge in rough set, finally, through a summary calculation, we get the composite score sort of bidding companies and the recommend the winning candidates. Combined with relevant case studies, the paper demonstrates the effectiveness and practicality of the model.