Solving Resource-Constrained Project Scheduling Problem via Genetic Algorithm

被引：40
|
作者：
Liu, Jia [1 ,2 ]
Liu, Yisheng [3 ]
Shi, Ying [4 ]
Li, Jian [5 ]
机构：
[1] China Construct Sci & Technol Changchun Co Ltd, Dept Engn Management, Changchun 130033, Peoples R China
[2] Beijing Jiaotong Univ, Sch Econ & Management, Beijing 100044, Peoples R China
[3] Beijing Jiaotong Univ, Dept Engn Management, Beijing 100044, Peoples R China
[4] China Univ Min & Technol Beijing, Sch Management, Beijing 100044, Peoples R China
[5] Natl Res Ctr Rehabil Tech Aids, Minist Civil Affairs, Beijing Key Lab Rehabil Tech Aids Old Age Disabil, Key Lab Intelligent Control & Rehabil Technol, Beijing 100176, Peoples R China
来源：
JOURNAL OF COMPUTING IN CIVIL ENGINEERING | 2020年 / 34卷 / 02期
关键词：
Construction management; Genetic algorithm; Resource-constrained project scheduling problem; PARTICLE SWARM OPTIMIZATION; BRANCH; HEURISTICS; GENERATION; SCHEMES; SERIAL;
D O I：
10.1061/(ASCE)CP.1943-5487.0000874
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The resource-constrained project scheduling problem (RCPSP) is an important and challenging problem in the field of construction management. This paper presents a genetic algorithm (GA) for the RCPSP. The proposed algorithm introduces several changes in the genetic algorithm paradigm, such as a new selection operator to select parents to recombine; a modified two-point crossover operator with a specific crossover order; and a linearly decreasing probability-based mutation operator. The proposed algorithm was tested using standard benchmark problems of size J30, J60, and J120 from Project Scheduling Problem Library (PSPLIB) and compared with 19 state-of-the-art metaheuristics in the literature. The computational results validate that the proposed algorithm is a competitive algorithm for solving the RCPSP.
引用
收藏
页数：10
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