DocumentCode :
2096788
Title :
A Genetic Algorithm for Solving RCPSP
Author :
Zhang, Hua ; Xu, Hao ; Peng, WuLiang
Author_Institution :
Sch. of Mech. Eng., Shenyang Ligong Univ. Shenyang, Shenyang, China
Volume :
2
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
246
Lastpage :
249
Abstract :
A genetic algorithm (GA) was proposed to solve the resource constrained project scheduling problem (RCPSP), in which resources are renewable and there is a single mode to perform each activity. This work employed genetic algorithms to schedule project activities to minimize make-span subject to precedence constraints and resources availability. In the genetic algorithm, a new permutation of priority-based encoding scheme was designed in the algorithm, and it inherits all the merits of both the permutation-based encoding scheme and the priority-based encoding scheme. The serial generation scheme was used in decoding scheme to generate project plan. A full factorial computational experiment was set up using the well-known standard instances in PSPLIB, and the algorithm given in this paper was compared with the existing intelligent optimization algorithms, the results reveal that the algorithm is effective for the RCPSP.
Keywords :
decoding; encoding; genetic algorithms; minimisation; project management; resource allocation; scheduling; decoding; factorial computational experiment; genetic algorithm; make-span minimization; permutation-based encoding scheme; precedence constraint; priority-based encoding scheme; project plan generation; renewable resource constrained project scheduling problem; resource availability; serial generation scheme; Algorithm design and analysis; Availability; Computer science; Decoding; Encoding; Genetic algorithms; Heuristic algorithms; Mechanical engineering; NP-hard problem; Processor scheduling; genetic algorithm; project scheduling; resource constrained project scheduling problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
Type :
conf
DOI :
10.1109/ISCSCT.2008.255
Filename :
4731613
Link To Document :
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