Ga-based resource leveling optimization for construction project

被引：0

作者：

Zhao, Sheng-Li ^{[1
]}

Liu, Yan ^{[1
]}

Zhao, Hong-Mei ^{[2
]}

Zhou, Ri-Lin ^{[1
]}

机构：

[1] Hebei Agr Univ, Rural & Urban Construct Coll, Baoding 071001, Peoples R China

[2] Hebei Agr Univ, Informat Sci & Technol Coll, Baoding 071001, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年

关键词：

resource leveling; genetic algorithms; optimization; construction project;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The objective of this paper is to present a GA-based optimal model for resource leveling problem, which overcomes the drawbacks of traditional resource leveling models. Based on the problem characteristics, the code scheme, genetic operators and algorithm structure of the proposed model are designed. By adopting several improved techniques, the GA-based model can determines the optimal solution to multiple resources leveling problems for a construction project. A case example is presented to demonstrate the performance of the GA-based model against heuristic methods.

引用

页码：2363 / +

页数：3

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