Online performance evaluation method and system based on nonlinear generating function and weight optimization

Abstract

The invention discloses an online performance evaluation method and system based on a nonlinear generating function and weight optimization. The method comprises the following steps that 1) performance data is filled; 2) according to the filled performance data, performance scores of different evaluated objects corresponding to different evaluation criteria are calculated, and an original score matrix X is obtained; 3) the original score matrix is standardized to obtain a standard score matrix Y of n rows and m columns; 4) a weight optimization model (MIN-MAX model) is established; 5) the weight optimization model is solved, and optimal evaluation criterion weight vectors are calculated; and 6) the standard score matrix Y in step 3) and the optimal criterion weight vectors in the step 5) are used to calculate a comprehensive performance score of all the evaluated objects. An evaluation result of the invention is objective, accurate and effective.

Description

technical field [0001] The invention relates to computer information management technology, in particular to an online performance evaluation method and system based on nonlinear generating function and weight optimization. Background technique [0002] Performance evaluation, also known as performance evaluation, performance appraisal, performance evaluation, employee appraisal, is a formal employee evaluation system and an important basic work in human resource development and management. Assess and measure employees' work behavior and work effectiveness in their positions. Commonly used performance evaluation (performance appraisal) methods are generally divided into: result-oriented performance evaluation methods, such as performance evaluation table method, objective management method, key performance indicator method, etc.; the evaluation made by such methods The main basis is the performance of the work, that is, the result of the work. Whether the task can be comple...

AI Technical Summary

Problems solved by technology

[0003] (1) In the existing evaluation system, when there are multiple participants in the same performance item, the most advanced method for the performance distribution of each participant is to calculate the performance of each participant based on the ranking order, often using a linear decreasing method, without considering the actual performance contribution The nonlinear characteristics of

[0004] (2) In the existing evaluation system, it is considered to use multiple indicators for comprehensive evaluation, but how to determine the weight of each indicator is a very critical issue. The existing evaluation system generally adopts a simple subjective assignment method, Or the method of variable coefficient is given, but the method of subjective assignment and given weight is too subjective and arbitrary. The variable coefficient method is for ranking and ranking, that is to say, the core idea of ​​its calculation method is to assign the weight of the index with the greatest degree of discrimination Largest value, lack of objective weight optimization method based on data

[0005] (3) When the existing evaluation system integrates multi-indicator data for ranking, weighted average is often used. In fact, whether the method of weighted average is applicable is debatable

[0006] (4) In the existing evaluation system, there is a lack of real-time dynamic monitoring when the evaluation objects fill in their own performance items;

[0007] (5) In the existing evaluation system, there is a lack of real-time "manager-evaluation object" interactive feedback based on mobile Internet technology when reviewing the performance items declared by the evaluation object and their supporting materials.

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