Multi Objective Optimization Method Of Small Water Conservancy Project Based On Improved AHP Grey Correlation

The general water conservancy construction project has the characteristics of relatively complex construction conditions,long construction period,and affected by the flood season.The construction of water conservancy projects is related to the safety of people’s lives and property,so the quality requirements are high.However,there are still many problems in the construction and management of grass-roots water conservancy facilities,such as: most of the construction units are government units,the investment amount is limited;The professional level of management personnel is low,and the progress management basically depends on experience.Due to the lack of progress control,there are often phenomena such as cross flood construction,rush and delay.This paper takes the multi-objective optimization method of small water conservancy project schedule as the research object,based on the network planning technology,uses the improved AHP grey correlation analysis method to solve the multi-objective optimization model,in order to find out the best construction plan that meets the preference of decision makers.Firstly,we analyzes the domestic and foreign literature on multi-objective optimization research and multi-objective decision-making method,and then establishes a multi-objective optimization model of construction period,cost,quality level,safety reliability and resource balance strength under the constraints of resources and construction period by consulting experts and combining with the construction status of small water conservancy projects,At the same time,the traditional AHP multi-objective algorithm is improved by learning from each other’s strong points,and AHP entropy grey relational analysis and FAHP entropy grey relational analysis based on index scale are proposed to solve the multi-objective optimization model.Finally,the proposed model and method are applied to Tuanjie xiangshuihe reservoir project for example verification.Considering the limitation of the network diagram,this paper draws the bar chart while drawing the network diagram of the main part of the project,introduces the proposed multi-objective optimization model,uses the network planning technology to optimize and adjust the working hours on the critical path and non critical path,calculates all the objective parameter values,obtains the optimal solution set,and then uses the improved algorithm to solve the problem and obtaines the optimal scheme of the project.By comparing the schemes,it is concluded that the AHP entropy grey correlation analysis method based on the index scale is easy to calculate,and the judgment matrix obtained is consistent,which is suitable for solving the multi-objective optimization model with obvious characteristics and few evaluation factors;The FAHP entropy grey relational analysis method is more suitable for the model with the characteristics of multi-level,multi factor and high demand of decision makers;The optimal scheme obtained by the two improved methods is consistent and obviously better than superior scheme.The main innovations of this study are as follows(1)Breaking the limitation of traditional algorithm and intelligent algorithm in multi-objective optimization target selection.A multi-objective optimization model of small water conservancy project with time limit,quality,cost,safety and resource balance is established from the perspective of decision-makers.(2)The limitation of traditional method is overcome by improving analytic hierarchy process.The entropy method is used to modify the initial weight to increase the quantitative analysis and improve the objectivity;The optimal solution is selected by grey correlation analysis to avoid unreasonable results due to low resolution;AHP and FAHP based on index scale are used to calculate the weight respectively,and the data checking,which makes the solution simple and quick,and increases the practicability and scientificity of the multi-objective optimization solution,provides choice space for decision-makers and researchers.