NDLI: Particle Swarm and Ant Colony Algorithms Hybridized for Multi-Mode Resource-constrained Project Scheduling Problem with Minimum Time Lag

Content Provider	IEEE Xplore Digital Library
Author	Shan Miyuan Wu Juan Peng Danni
Copyright Year	2007
Description	Author affiliation: Sch. of Bus. Adm., Hunan Univ., Changsha (Shan Miyuan; Wu Juan; Peng Danni)
Abstract	MMRCPSP/MIN has been proved to be a NP-hard problem. Based on the introduction of model of project scheduling problem with minimum time lag developed by Roland Heilmann, the paper analyzed two swarm intelligence algorithms which have good performance in solving combinatorial optimization problem-ACO and PSO algorithms. Based on analysis of these algorithms' defects, the paper proposed that the defects of ACO algorithm such as hard to converge, performance significantly affected by parameters, high requirement for parameters and so on, can be made up by the high convergence of PSO algorithm. The parameters of ACO algorithm were set in terms of the solution of PSO algorithm. Through particle swarm iteration and making convergence effect and better objective solution of ACO algorithm as fitness value in order to lead the optimization of particle swarm, we can obtain the optimal solution as well as better convergence speed and effect. Finally, the model and problem solving process were programmed in the C++ language. Intensive computational experiments were done on cases in PSPLIB. The result shows that with the iteration of PSO algorithm, both the performance and convergence of ACO algorithm are improved.
Starting Page	5898
Ending Page	5902
File Size	222090
Page Count	5
File Format	PDF
ISBN	9781424413119
DOI	10.1109/WICOM.2007.1446
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Ant colony optimization NP-hard problem Processor scheduling Project management Performance analysis Problem-solving Particle swarm optimization Scheduling algorithm Convergence
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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