A Genetic Algorithm for Solving RCPSP

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 prec...

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Bibliographic Details
Published in:Proceedings : International Symposium on Computer Science and Computational Technology ; ISCSCT 2008 ; Shanghai, China, 20-22 December 2008 Vol. 2; pp. 246 - 249
Main Authors: Hua Zhang, Hao Xu, Wuliang Peng
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2008
Subjects:
Algorithm design and analysis
Availability
Computer science
Decoding
Encoding
genetic algorithm
Genetic algorithms
Heuristic algorithms
Mechanical engineering
NP-hard problem
Processor scheduling
project scheduling
resource constrained project scheduling problem
ISBN:1424437466, 9781424437467, 9780769534985, 0769534988
Online Access:Get full text
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Summary: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.
ISBN:1424437466
9781424437467
9780769534985
0769534988
DOI:10.1109/ISCSCT.2008.255