The Study Of Trade-off Optimization In Construction Project Based On Kuzzy Programming

The success and failure of complex construction project not only determines theexistence of all corporations but also has a great affection on the national economy.With the development of tendency that modern construction projects are becomingbigger and more complex, uncertain factor urgently need to be considered inengineering optimization. So traditional optimal method can’t meet and fit the demandsof complex construction project management. A new and adjusted optimal idea andmethod is urgently needed. Fuzzy programming theory provides some new forms tostudy construction project management. It is an effective way to combine fuzzyprogramming theory and project management to study complex construction projectmanagement.This paper is based on fuzzy theory, net planning technology, introduces thecredibility theory, deeply analyzes the trade-off optimization in construction projectbuilds corresponding mathematical programming model according to differentdecision-making criteria and respectively designs the hybrid intelligent algorithm. Themajor works of this paper include:(1) It studies the problem of time optimization in construction project in fuzzyenvironment. At first, it describes the uncertainty of activity duration times usingtriangular fuzzy numbers, builds three fuzzy models of time optimization under theconstraint of cost: expected duration minimization model, duration thresholdsminimization model and duration credibility maximization model; Secondly, itintegrates fuzzy simulations, neural network and genetic particle swarm algorithm todesign a hybrid intelligent algorithm，which is stable to solve the three models; At last,it verifies rationality and practicality of the models by the case.(2) It studies fuzzy trade-off optimization of multi-model time-cost-quality. At first,it describes the uncertainty of activity duration times, needful cost, obtainable qualityand the weight of quality in different modes using triangular fuzzy numbers, buildsfuzzy expected value model of multi-model time-cost-quality trade-off optimization;The next, it integrates fuzzy simulation, neural network and multi-objective particleswarm algorithm to design a hybrid intelligent algorithm，which is stable to solve the model; Further, it verifies rationality and practicality of the models by the illustration.(3) It studies fuzzy trade-off optimization of linear time-cost-quality. At first, itdescribes the uncertainty of activity normal finish time using triangular fuzzy numbers,builds three fuzzy models of linear time-cost-quality trade-off optimization: fuzzyexpected value model, fuzzy chance-constrained programming model and fuzzydependent-chance programming model; And then, it integrates fuzzy simulations, neuralnetwork and multi-objective particle swarm algorithm to design a hybrid intelligentalgorithm，which is stable to solve the models; At last, it verifies rationality andpracticality of the models by the examples.