Genetic Algorithm-based Chaos Clustering Approach for Optimizing Construction Timecosttradeoff Problems

نویسندگان

  • Min-Yuan Cheng
  • Kuo-Yu Huang
چکیده

Time-cost tradeoff (TCT) problems have been studied extensively in construction management literatures. TCT decisions, as combinatorial optimization problems, are difficult to find out their optimal solutions. However, Genetic Algorithms (GA) coupled with chaos and K-means clustering approach, named KCGA, can tackle these problems effectively. KCGA has successfully incorporated two opposite properties contraction and diversity which come from Kmeans and chaos, respectively. K-means is to speed up the contraction and chaos to diversify population in GA. The hybrid KCGA approach was verified by empirical construction management example with excellent performance in terms of computation efficiency and estimation accuracy while comparing with other algorithms separately.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Solving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

متن کامل

Solving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

متن کامل

Data Clustring Using A New CGA(Chaotic-Generic Algorithm) Approach

Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...

متن کامل

Data Clustring Using A New CGA(Chaotic-Generic Algorithm) Approach

Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...

متن کامل

Tabu-KM: A Hybrid Clustering Algorithm Based on Tabu Search Approach

  The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011