摘要
To solve the resource-constrained project scheduling problem （RCPSP）, a hybrid ant colony optimization （HACO） approach is presented. To improve the quality of the schedules, the HACO is incorporated with an extended double justification in which the activity splitting is applied to predict whether the schedule could be improved. The HACO is tested on the set of large benchmark problems from the project scheduling problem library （PSPLIB）. The computational result shows that the proposed algo- rithm can improve the quality of the schedules efficiently.
To solve the resource-constrained project scheduling problem （RCPSP）, a hybrid ant colony optimization （HACO） approach is presented. To improve the quality of the schedules, the HACO is incorporated with an extended double justification in which the activity splitting is applied to predict whether the schedule could be improved. The HACO is tested on the set of large benchmark problems from the project scheduling problem library （PSPLIB）. The computational result shows that the proposed algo- rithm can improve the quality of the schedules efficiently.
基金
supported by Liaoning BaiQianWan Talents Program(20071866-25)
作者简介
Corresponding author.Linyi Deng was born in 1978. She received her Ph.D. from Dalian University of Technology in 2008. Her research interests are resource-constrained project schedule problem, resource allocation and intelligent computation. E-mail：hsdly@ 163.comYah Lin was born in 1963. He was entered into the Cross-Centuary Excellent Talented of China government. He is an excellent expert of Dalian Government. His current research interest is intelligent CAD. E-mail：linyan@dlut.edu.cnMing Chert was born in 1972. He is an associate professor and Ph.D. tutor. His current research interests are computer-aided ship design, project schedule and intelligent computation. E-mail：chenming @ dlut.edu.cn
