Research And Development Of Evaluation Experts Management System Based On Genetic Algorithm

Management and utilization of expert evaluation is an important link of biddingwork, and unified experts regulatory could improve the scientificalness and thefairness of the bidding activities. The method of expert extraction is studied, to betterreflect the randomness and the fairness of the expert extraction. In this thesis, on thebasis of this, the development of evaluation expert management system, it plays animportant role for improving the work quality and management level.This thesis studies the bidding policies and regulations，reviews the relevanttheory and technology, such as fuzzy comprehensive evaluation method, the theory ofintelligent algorithm, genetic algorithm. Based on customer demand analysis andresearching on the expert extraction algorithm, this thesis establishes themathematical model of expert selection, establishes the fitness function and theconvergence criteria. Based on the genetic algorithm process, experiments are carriedout to, this thesis designs the simulation experiment, experimental results show thatthis model has better random and fairness. This thesis completes the analysis ofevaluation expert management system needs analysis: analysis of expert informationmanagement, expert extraction and project management process, analysis of thesystem function use case, analysis of the system fairness, stochastic demand. Thisthesis studies the system design principle and completes the system architecturedesign, database design, system function module design and the page design. Thisthesis introduces the implementation of expert database management module andproject bidding expert extraction module in detail.At present, the key part of evaluation expert management system has beencompleted. The work has reached the expected requirements and has been recognizedby the user. With the systematic application of in-depth, the system need to be furtherimproved, in order to meet user needs.