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Combinatorial versus Priority Based Optimization in Resource Constrained Project Scheduling Problems by Nature Inspired MetaheuristicsBEJINARIU, S.-I. , COSTIN, H. , COSTIN, D.
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biological information theory, evolutionary computation, optimization, particle swarm optimization, scheduling algorithms
optimization(18), algorithm(11), swarm(8), scheduling(7), flower(7), costin(7), yang(6), science(6), problem(6), pollination(6)
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About this article
Date of Publication: 2019-02-28
Volume 19, Issue 1, Year 2019, On page(s): 17 - 26
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.01003
Web of Science Accession Number: 000459986900003
SCOPUS ID: 85064227660
This paper explores the behavior of the Flower Pollination Algorithm (FPA) and Particle Swarm Optimization (PSO) metaheuristic algorithm in resolving Resource Constrained Project Scheduling Problems (RCPSP) that can model certain practical issues in distributed applications. A RCPSP type problem has at the input a set of activities between which there are precedence relationships and for whose execution it is necessary to allocate resources that are limited. The solution determines the order of execution of the activities with respect to the precedence relations between them and the allocation of the available resources so that the total duration is minimal. The experimental results showed that a near optimal solution can be obtained faster than with other traditional algorithms, mainly for optimization problems in the continuous space. Two versions of FPA and PSO were used, namely combinatorial and priority based optimization. Because during evolution the individuals position changes do not guarantee the precedence order preservation, a new tasks reordering procedure is proposed in this paper.
|References|||||Cited By «-- Click to see who has cited this paper|
| M. Cisse, S. Yalçindag, Y. Kergosien, E. Sahin, C. Lente, A. Matta, "OR problems related to home health care: a review of relevant routing and scheduling problems", Operations Research for Health Care, Vols. 13-14, pp. 1-22, 2017, |
[CrossRef] [Web of Science Times Cited 92] [SCOPUS Times Cited 115]
 R. M. Chen, C. L. Wub, C. M. Wang, S. T. Lo, "Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in PSPLIB", Expert Systems with Applications, Vol. 37, pp. 1899-1910, 2010,
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 57]
 M. Eddaly, B. Jarboui, P. Siarry, "Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem", Journal of Computational Design and Engineering, Vol. 3, pp. 295-311, 2016,
[CrossRef] [SCOPUS Times Cited 50]
 H. Zhang, H. Li, C.M. Tam, "Particle swarm optimization for resource-constrained project scheduling", International Journal of Project Management, Vol. 24, pp. 83-92, 2006,
[CrossRef] [SCOPUS Times Cited 139]
 K. Bibiks, J. P. Li, F. Hu, "Discrete flower pollination algorithm for resource constrained project scheduling problem", International Journal of Computer Science and Information Security, Vol. 13(7), pp. 8-19, 2015.
 X.-S. Yang, "Flower pollination algorithm for global optimization", in Unconventional Computation and Natural Computation, Lecture Notes in Computer Science, Vol. 7445, pp. 240-249, 2012,
[CrossRef] [SCOPUS Times Cited 1459]
 E. Emary, H. M. Zawbaa, A. E. Hassanien, B. Parv, "Multi-objective retinal vessel localization using flower pollination search algorithm with pattern search", Advances in Data Analysis and Classification, Vol. 11, No. 3, pp. 611-627, 2017,
[CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 21]
 R. Wang, Y. Zhou, C. Zhao, H. Wu, "A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation", Bio-Medical Materials and Engineering, Vol. 26, pp. 1345-1351, 2015,
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 38]
 S. M. Nigdeli, G. Bekdas, X.-S. Yang, "Application of the flower pollination algorithm in structural engineering", in X.-S. Yang et al. (Eds.), Metaheuristics and Optimization in Civil Engineering, Modeling and Optimization in Science and Technologies, Vol. 7, Springer, pp. 25-42, 2016,
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 46]
 A. Goli, A. Aazami, A. Jabbarzadeh, "Accelerated cuckoo optimization algorithm for capacitated vehicle routing problem in competitive conditions", International Journal of Artificial Intelligence, vol. 16, no. 1, pp. 88-112, Mar. 2018.
 J. Ruiz-Rangel, C. J. Ardila Hernandez, L. M. Gonzalez, D. J. Molinares, "ERNEAD: training of artificial neural networks based on a genetic algorithm and finite automata theory", International Journal of Artificial Intelligence, vol. 16, no. 1, pp. 214-253, Mar. 2018.
 S.-I. Bejinariu, H. Costin, F. Rotaru, R. Luca, C. Nita, C. Lazar, "Parallel processing and bio-inspired computing for biomedical image registration", Computer Science Journal of Moldova, Vol. 22, No. 2(65), pp. 253-277, 2014.
 H. Costin, S.-I. Bejinariu, "Medical image registration by means of a bio-inspired optimization strategy", Computer Science Journal of Moldova, Vol. 20, No. 2(59), pp. 178-202, 2012.
 H. Costin, S.-I. Bejinariu, D. Costin, "Biomedical image registration by means of bacterial foraging paradigm", International Journal of Computers, Communications & Control, Vol. 11, No. 3, pp. 329-345, 2016,
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]
 S.-I. Bejinariu, H. Costin, F. Rotaru, R. Luca, C. Nita, "Image processing by means of some bio-inspired optimization algorithms", Proc. of the IEEE 5th Int. Conference on E-Health and Bioengineering - EHB 2015, Iasi, România, 2015, pp. 1-4,
[CrossRef] [SCOPUS Times Cited 8]
 S.-I. Bejinariu, R. Luca, H. Costin, "Nature-inspired algorithms based multispectral image fusion", Proc. of the 2016 International Conference and Exposition on Electrical and Power Engineering, Iasi, România, pp. 1-5, 2016,
[CrossRef] [SCOPUS Times Cited 22]
 S.-I. Bejinariu, H. Costin, F. Rotaru, R. Luca, C. Nita, "Performance analysis of artificial bee colony optimization algorithm", in Proc. of the 13-th Int. Symposium on Signals, Circuits and Systems, ISSCS 2017, Iasi, România, pp. 1-4, 2017,
[CrossRef] [SCOPUS Times Cited 2]
 X.-S. Yang, Nature-Inspired Optimization Algorithms. Elsevier Inc., pp. 23-173, 2014, ISBN: 0124167438 9780124167438.
 J. Kennedy, R. Eberhart, "Particle swarm optimization", Proc. of the IEEE Int. Conference on Neural Networks, Perth, WA, Australia, Vol. 4, pp. 1942-1948, 1995,
[CrossRef] [Web of Science Times Cited 27920]
 T. Hendtlass, "WoSP: a multi-optima particle swarm algorithm", Proc. of the IEEE Congress on Evolutionary Computation, Edinburgh, Scotland, UK, pp. 727-734, 2005,
 X.-S. Yang, M. Karamanoglu, X.S. He, "Flower pollination algorithm: a novel approach for multiobjective optimization", Engineering Optimization, Vol. 46, No. 9, pp. 1222-1237, 2014,
[CrossRef] [Web of Science Times Cited 339] [SCOPUS Times Cited 429]
 X.-S. Yang, M. Karamanoglu, X.S. He, "Multi-objective flower algorithm for optimization", Procedia Computer Science, Vol. 18, pp. 861-868, 2013,
[CrossRef] [Web of Science Times Cited 198] [SCOPUS Times Cited 275]
 B. Jarboui, M. Cheikh, P. Siarry, A. Rebai, "Combinatorial particle swarm optimization (CPSO) for partitional clustering problem", Applied Mathematics and Computation, Vol. 192, pp. 337-345, 2007,
[CrossRef] [Web of Science Times Cited 73] [SCOPUS Times Cited 102]
 B. Jarboui, N. Damak, P. Siarry, A. Rebai, "A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems", Applied Mathematics and Computation, Vol. 195, pp. 299-308, 2008,
[CrossRef] [Web of Science Times Cited 211] [SCOPUS Times Cited 272]
 PSPLIB, Project Scheduling Problem Library - PSPLIB, http://www.om-db.wi.tum.de/psplib/main.html (Accessed 4 December 2017).
 R. C. Eberhart. Y. Shi, "Comparing inertia weights and constriction factors in particle swarm optimization", Proc. of the Congress on Evolutionary Computation, La Jolla, CA, USA, Vol. 1, pp. 84-88, 2000,
[CrossRef] [SCOPUS Times Cited 2655]
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