Research And Application Of Multi-objective Decision In Engineering Project Based On Intelligent Computing

With the increasing emphasis on the implementation of engineering projects and the development of multi-objective optimization,the multi-objective decision-making of engineering projects has become a hot research topic.The traditional multi-objective system of engineering projects includes three major goals: construction period,cost and quality.However,with the increasing awareness of environmental protection and personal safety,the system can no longer meet people’s needs.How to enrich the multi-objective management system,how to achieve multi-objective optimization in engineering projects and how to carry out multi-objective decision-making of engineering projects scientifically have become research hotspots in the field of engineering project management.At the same time,with the increase of engineering project construction scale and investment scale,traditional mathematical methods have difficulty in solving those multi-objective engineering problems.When solving multi-objective optimization problems,intelligent algorithms such as genetic algorithm are vulnerable to other variables so they are tend to be trapped in local optimum.Therefore,this paper explores intelligent algorithms with few parameters,simple structure,good optimization performance and high robustness to solve multi-objective problems of engineering projects.In view of the problem that the multi-objective management system is not perfect,this paper enriches the connotation of each engineering objective and establishes a engineering objectives management system covering the construction period,cost,quality,safety and environmental protection level.It also focuses on the coordination of the five major objectives.In this paper,five objectives are quantified reasonably,and optimal sub-models of construction period,construction period-cost,construction period-quality,safety level and construction period-environmental protection level are established respectively.Finally,a multi-objective optimization model of engineering project is synthesized.In order to effectively solve the multi-objective optimization model,this paper attempts to use the whale optimization algorithm to solve it.In order to improve the slow convergence rate and low stability of WOA,elite opposition-based golden-sine whale optimization algorithm is proposed.Elite opposition-based learning strategy is used to improve the diversity and quality of the population so that the convergence rate can be promoted.At the same time,golden-sine mechanism is introduced to improve the optimal method of WOA,so as to ocoordinate the global exploration and local exploitation.And various simulation experiments show the improved algorithm is effective and feasible.Multi-objective optimization of engineering project is a multi-objective problem.In order to better solve the problem,this paper introduces external archives and grid mechanism to elite opposition-based golden-sine whale optimization algorithm,and multi-objective elite opposition-based golden-sine whale optimization algorithm is proposed.Finally,the proposed multi-objective elite opposition-based golden-sine whale optimization algorithm is applied to engineering project examples,and diverse multi-objective optimization schemes are obtained,which provid decision makers with various schemes.According to the required construction period,cost,quality,safety and environmental protection levels,the project decision makers can select the best alternatives and allocate reasonable resources to each process.This paper provides innovative solutions for multi-objective decision-making of engineering projects,which can make decision-making more intelligent and scientific.This can provide managers with a variety of options to support decision-making,and to some extent reduce the management burden.