关键词: 大型工程, 资源匹配, 前景理论, 证据推理

Abstract: With the increasing demand for infrastructure construction, large-scale engineering construction has had opportunities for rapid development, but consumed a large amount of resources, including funds, manpower, materials, and machinery, etc. Due to the complexity of large-scale engineering construction tasks and the need for specialized division of labor, there are often dozens of construction enterprises in operation together. If the resources management is not coordinated, it would easily lead to project delays and losses. In practice, decision makers optimize resources allocation by considering the matching relationship among resources, which could promote the derivation of incremental benefits. However, large-scale engineering resources allocation is faced with a complex decision-making environment, and decision makers have to consider the adaptability of schemes in various situations. Even the same scheme may produce divergent or even opposite results in different situations. Moreover, large-scale engineering resources are always heavily invested in, and there are various influencing factors during the implementation process. Decision makers could make corresponding judgments based on accumulated experience and information. Their actual behavior is often irrational, and they exhibit a risk aversion awareness when facing higher than expected returns, and a risk tendency when facing losses that exceed expectations. Therefore, based on the “irrational” behavior preference of decision makers, choosing an effective resources matching scheme under uncertain situations is an important problem to be solved in project management.
This research introduces the concept of matching to large-scale engineering resources management. Decision makers need to consider the superiority of matching scheme from multiple perspectives, which means that the evaluation should have the characteristics of comprehensiveness. Relevant literature and expert experience are used to identify and screen multi-attribute indicators in the process. And the psychological expectations of decision makers are considered when evaluating attribute indicators. If the benefits of implementing matching scheme are higher or the costs are lower than corresponding expected values, the decision-maker's perception is a benefit, or otherwise, decision-maker's perception is a loss. According to the prospect theory, the irrationality is transformed into the sensitive attitude of decision-making process towards profit and loss, and the value function is introduced into decision matrix. Then, the mixed attribute judgment information is normalized into a unified form to eliminate the difference. Based on this, the identification framework of multi-attribute index of resources matching scheme is constructed. Due to the limited experience and cognition of decision makers, the lower and upper limits of the weights of each indicator are represented by intervals. Finally, the evidence reasoning algorithm and ER rules are used to synthesize the multi-attribute foreground decision matrix and weight information, as evidence for determining the comprehensive prospect value of each resources matching scheme.
To illustrate the effectiveness of the method proposed in this research, a case is used to validate the evaluation model for large-scale engineering resources matching decision-making. After obtaining relevant data, a comprehensive prospect ranking of each scheme is calculated based on the decision-making steps. The results show the difference in scheme rankings under different situations, indicating the effectiveness of the decision-making method. It makes the research results more in line with the behavior of decision makers in reality. Different from the prospect theory, expected utility studies the choices of rational people under uncertain conditions through strict axiomatic assumptions. It believes that decision makers can make rational judgments when facing various risks and weight all possible outcomes to maximize expected utility. Therefore, this paper also compares the decision results based on the prospect theory and expected utility theory, and verifies the feasibility and effectiveness of the large engineering resources matching decision method. In conclusion, this method could integrate multi-attribute mixed decision information, and consider the factors of decision maker's psychology and situation change. It provides theoretical reference for resources decision-making in project management and engineering practice.

Key words: large-scale engineering, resource collaborative, prospect theory, evidential reasoning