The Study Of Multi-objective Trade-off Optimization In Highway Project Based On Fuzzy Random Programming

In recent years,China’s investment in highway construction projects increased significantly,indicating that the county’s attention to the highway project greatly improved.The previous research on the engineering project is just single-objective optimization,it is mainly the optimization of construction time,cost optimization or making time and cost as a whole to optimize comprehensively.However,in recent years,researchers add quality objective to the project optimization,thus,the optimization of engineering project has been formed three goals,and researchers need to optimize them comprehensively.In order to make the project managers to arrange the duration of the activities reasonably,the paper uses different method form the methods of traditional multi-objective optimization,and places highway engineering optimization in fuzzy random environment that more realistic,and uses fuzzy random programming to build time optimization models and time-cost-quality trade-off optimization models.In this process,the paper finishes the transition from single-objective optimization to multi-objective optimization,and designs hybrid intelligent algorithm correspondingly to solve those models.The main contents of the paper are as follows:Firstly,optimizing the time goal of the highway engineering in fuzzy random environment,aiming at establishing reasonable optimization models of time,and using the designed hybrid intelligent algorithm to get the best change of the activities duration.In this part,using triangular fuzzy random variable to represent the normal duration of the activities that is not affected by the decisions that project managers make.The decision variable is used to indicate the change of the activities duration that is affected by the decisions that project managers make.In order to optimize time goal,using the time as the objective function,and cost as the constraint condition,the expected value model,chance-constrained programming model and dependent-chance programming model are established by using fuzzy random programming theory,and using a hybrid intelligent algorithm that combining fuzzy stochastic simulation and genetic algorithm to solve these models.Secondly,the optimization of time-cost-quality trade-off optimization of highway project in fuzzy random environment is carried out.The aim is to establish a reasonable multi-objective trade-off optimization model and use the designed hybrid intelligent algorithm to obtain the better crashing time.In this section,the triangular fuzzy random variable also represents the normal duration of the activities that is not affected by the decision that project managers make,and the decision variable represents the crashing time of the activities.According to the actual project management and the given assumption,time function,cost function and quality function are obtained.Then,establishing three models related to fuzzy random programming.By means of genetic multi-objective optimization method and Pareto ranking,the hybrid intelligent algorithm combining fuzzy stochastic simulation and genetic algorithm is designed to solve those models.Finally,by first example,three time optimization models of the highway project in fuzzy random environment are established respectively.Using the hybrid intelligent algorithm to solve models to get the change of activities duration,and time is calculated correspondingly,thus the rationality and validity of the models is verified.The second example is given to establish three multi-objective trade-off optimization models.By using the hybrid intelligent algorithm,the Pareto solution of the crashing time is obtained,and the time,cost and quality are calculated correspondingly,so as to verify the rationality and validity of the models.