Decision Model of Engineering Bid Evaluation and Its Application under Uncertain Information Environment

Abstract

In this paper, the decision problem of engineering bid evaluation is studied, and a decision model of engineering bid evaluation is presented based on the method of grey correlation analysis. In this model, all evaluation attribute values are transformed into interval numbers, then a grey correlation degree of interval number sequence is defined to rank all alternative bids. Moreover, an engineering bid evaluation example is given to show the feasibility and effectiveness of this decision model. Introduction On January 1, 2000, the bidding law of the People's Republic of China was formally implemented, since then the bidding management of our country's engineering construction project marched into the legalization management track. In the legal system of bidding management, one of the important works is engineering bid assessment. The evaluation process is to select the optimal bid from all tenders. Along with the increasing standardization of bidding management, the evaluation is no longer just is the comparison of the engineering quotation, but to multiple index comprehensive evaluation for all tenders [1-5]. Therefore, how to establish a scientific evaluation method to conduct the bidding assessment work, this is an important subject related to engineering construction management [6-8]. In this paper, we study the decision problem of engineering bid evaluation, and present a decision model of engineering bid evaluation based on the method of grey correlation analysis. We try to provide a new scientific and effective quantitative method for engineering bid evaluation work in practical. Decision Model of Engineering Bid Evaluation The problem of engineering bid evaluation can be described as follows. A department of construction management will organize a project bidding, and there are m bidders submit bids, which denoted as 1 2 , ,..., m x x x . Six evaluation attributes are given to evaluate the m bids, i.e., G1 bid price (ten thousand yuan), G2 delivery time (months), G3 the main needed materials (ten thousand yuan), G4 the construction plan, G5 the quality performance and G6 corporate reputation. The weight wi of attribute Gi satisfies the conditions [ , ] j j j w c d ∈ , where 0 1 j j c d ≤ ≤ ≤ , 1, 2,..., j n = , and 1 2 ... 1 n w w w + + + = . The value of attribute j G for bid xi is denoted as aij, and the original decision matrix is denoted as A= (aij)m×6. From the information of matrix A, our goal is to select an optimal bidder among m bidders to do this engineering project. Now a decision model of engineering bid evaluation is presented based on the method of grey correlation analysis to solve the decision problem of engineering bid evaluation. The decision steps are given as follows. (1) Transform all evaluation attribute values into interval numbers. In the practical decision making, there are three types data for the above six evaluation attributes given by the decision makers, i.e., the evaluation values of G1 and G3 are given in the form of International Conference on Materials Engineering and Information Technology Applications (MEITA 2015) © 2015. The authors Published by Atlantis Press 324 precision numbers, the evaluation values of G2 are given in the form of interval numbers, and the evaluation values of G4, G5 and G6 are generally in the form of linguistic fuzzy numbers such as “very good, good, common, poor, very poor” or “very high, high, common, low, very low”. For a precision number aij, the corresponding interval number is [aij, aij]. For the linguistic fuzzy numbers such as “very good, good, common, poor, very poor” or “very high, high, common, low, very low”, the method of transforming them into interval numbers are given as follows. very good=[80, 100], good=[60, 80], common=[40, 60], poor=[20, 40], very poor=[0, 20]; very high=[80, 100], high=[60, 80], common=[40, 60], low=[20, 40], very low=[0, 20]. Based on the above transformed method, suppose that the value of aij attribute j G on xi is transformed into interval number , ij ij a a − +     , j=1, 2, ..., 6, then the original matrix A becomes