References



 
  1. Myszkowski P.B., Laszczyk M., "Investigation of benchmark dataset for many–objective Multi–Skill Resource Constrained Project Scheduling Problem", Applied Soft Computing, Applied Soft Computing, Volume 127, 2022, 109253,
    https://doi.org/10.1016/j.asoc.2022.109253

  2. M.Antkiewicz, P.B.Myszkowski, M.Laszczyk, "GaMeDE2—improved Gap–based Memetic Differential Evolution applied to Multimodal Optimization", 2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS 2022) DOI: https://doi.org/10.15439/2022F153
     
  3. Myszkowski P.B., Laszczyk M., "Diversity based selection for many-objective evolutionary optimisation problems with constraints", Information Sciences 546 (2021) 665–700, https://doi.org/10.1016/j.ins.2020.08.118
     
  4. Laszczyk M., Myszkowski P., "A Gap–based Memetic Differential Evolution (GaMeDE) applied to multi–modal optimisation – using multi–objective optimization concepts", ACIIDS 2021 (best student paper). 13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021.
     
  5. Paweł B. Myszkowski, Maciej Laszczyk, Kamil Dziadek, Non–dominated Sorting Tournament Genetic Algorithm for Multi-Objective Travelling Salesman Problem,
    FEDCsis Conference 2019, AAiA, DOI: http://dx.doi.org/10.15439/2019F192

    6.  
  6. Maciej Laszczyk Paweł B. Myszkowski A Specialized Evolutionary Approach to bi--objective Travelling Thief Problem
    FEDCsis Conference 2019, AAiA, DOI: https://annals-csis.org/Volume_18/drp/191.html

    7.  
  7. Laszczyk M., Myszkowski P.B., "Survey of quality measures for multi-objective optimization. Construction of complementary set of multi-objective quality measures" Swarm and Evolutionary Computation, Volume 48, August 2019, Pages 109-133.
    https://doi.org/10.1016/j.swevo.2019.04.001

    8.  
  8. Laszczyk M., Myszkowski P.B., "Improved selection in evolutionary multi-objective optimization of Multi-Skill Resource-Constrained Project Scheduling Problem", Information Science, Volume 481, May 2019, Pages 412-431
    https://doi.org/10.1016/j.ins.2019.01.002
    Simple comparision of NSGA-II and NTGA -- here (animated GIF, ~3,2MB)

    9.  
  9. Myszkowski, P.B., Laszczyk, M., Nikulin, I. et al. "iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained Project Scheduling Problem", Soft Comput (2019) 23: 3397.
    https://doi.org/10.1007/s00500-017-2997-5
    Note: files presented in publication are in library section.

    10.  
  10. Myszkowski P.B., Olech L.P., Laszczyk M. and Skowroński M.E. "Hybrid Differential Evolution and Greedy (DEGR) for Solving Multi–Skill Resource–Constrained Project Scheduling Problem", Applied Soft Computing, 2018,
    DEGR iMOPSE DO (Duration Optimisation) results
     
  11. Myszkowski P.B., Laszczyk M. and Lichodij J. "Efficient selection operators in NSGA-II for Solving Bi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem", Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 83–86 (2017).
    DOI: http://dx.doi.org/10.15439/2017F317 (+PDF)
     
  12. Myszkowski P.B., Laszczyk M. and Kalinowski D. "Co-Evolutionary Algorithm solving Multi-Skill Resource-Constrained Project Scheduling Problem", Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 75–82 (2017) DOI: http://dx.doi.org/10.15439/2017F318 (+PDF)
     
  13. Myszkowski P.B., Siemienski J.J., "GRASP applied to Multi-Skill Resource-Constrained Project Scheduling Problem", Computational Collective Intelligence, Volume 9875 of the series Lecture Notes in Computer Science pp.402-411
    DOI: 10.1007/978-3-319-45243-2_37
    GRASP best iMOPSE DO (Duration Optimisation) results
     
  14. Myszkowski P.B., Skowroński M., Sikora K., "A new benchmark dataset for Multi-Skill Resource-Constrained Project Scheduling Problem", Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 5, pages 129–138 (2015)
    DOI:http://dx.doi.org/10.15439/2015F273
     
  15. Myszkowski P., Skowroński M., Olech L., Oślizło K. "Hybrid Ant Colony Optimization in solving Multi–Skill Resource–Constrained Project Scheduling Problem", Soft Computing Journal, 2015, Volume 19, Issue 12, pp.3599–3619
    DOI: 10.1007/s00500-014-1455-x.
    https://arxiv.org/abs/1603.08538
     
  16. Myszkowski P., Skowroński M., "Specialized genetic operators for Multi–Skill Resource–Constrained Project Scheduling Problem", 19th International Conference on Soft Computing – Mendel 2013, pp. 57-62, 2013. [PDF, 622KB]
     
  17. Skowroński M., Myszkowski P., Kwiatek P., Adamski M., "Tabu Search approach for Multi–Skill Resource–Constrained Project Scheduling Problem", Annals of Computer Science and Information Systems Volume 1, Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, pp. 153-158, 2013.
     
  18. Skowroński M., Myszkowski P., Podlodowski Ł., "Novel heuristic solutions for Multi–Skill Resource–Constrained Project Scheduling Problem", Annals of Computer Science and Information Systems Volume 1, Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, pp. 159-166, 2013.

Citations

Last update
10.10.2017 		All citations included here.

  1. Parisa Shahnazari-Shahrezaei, Sina Zabihi, Reza Kia, Solving a Multi-Objective Mathematical Model for a Multi-Skilled Project Scheduling Problem by Particle Swarm Optimization and Differential Evolution Algorithms, Industrial Engineeering & Management Systems, Vol.16 No.3, 2017.9, pp.288-306
     
  2. Mohammad Rostami; Morteza Bagherpour; Mohammad Mahdavi Mazdeh; and Ahmad Makui, Resource Pool Location for Periodic Services in Decentralized Multi-Project Scheduling Problems, Journal of Computing in Civil Engineering, Volume 31 Issue 5 - September 2017, https://doi.org/10.1061/(ASCE)CP.1943-5487.0000671
     
  3. M. W. Przewozniczek, "Problem Encoding Allowing Cheap Fitness Computation of Mutated Individuals," 2017 IEEE Congress on Evolutionary Computation (CEC), San Sebastian, 2017, pp. 308-316. doi: 10.1109/CEC.2017.7969328
     
  4. Hamidreza Maghsoudlou, Behrouz Afshar-Nadjafi, Seyed Taghi, Akhavan Niak, Multi-skilled project scheduling with level-dependent rework risk; three multi-objective mechanisms based on cuckoo search, Applied Soft Computing Volume 54, May 2017, Pages 46-61, https://doi.org/10.1016/j.asoc.2017.01.024
     
  5. Yifei Ren, Zhiqiang Lu, Modeling and optimization of multi-skill resource investment problem considering workload balancing of resources Mechatronics and Automation (ICMA), 2017 IEEE International Conference on, DOI: 10.1109/ICMA.2017.8015901
     
  6. Javier Calle, Jesica Rivero, Dolores Cuadra, PedroIsasi, Extending ACO for fast path search in huge graphs and social networks, Expert Systems with Applications Volume 86, 15 November 2017, Pages 292-306, https://doi.org/10.1016/j.eswa.2017.05.066
     
  7. Karol Walȩdzik, Jacek Mańdziuk, Applying hybrid Monte Carlo Tree Search methods to Risk-Aware Project Scheduling Problem, Information Sciences Journal, https://doi.org/10.1016/j.ins.2017.08.049
     
  8. Ling Wang, Xiao-long Zheng, A knowledge-guided multi-objective fruit fly optimization algorithm for the multi-skill resource constrained project scheduling problem, Swarm and Evolutionary Computation xxx (xxxx) xxx–xxx, 2017. DOI: http://dx.doi.org/10.1016/j.swevo.2017.06.001
     
  9. Javier Calle, Jesica Rivero, Dolores Cuadra, Pedro Isasi, Extending ACO for fast path search in huge graphs and social networks, Expert Systems With Applications 86 (2017) 292–306, 2017. DOI: http://dx.doi.org/10.1016/j.eswa.2017.05.066
     
  10. Maghsoudlou, H., Afshar-Nadjafi, B., Akhavan Niaki, S.T., Multi-skilled project scheduling with level-dependent rework risk; three multi-objective mechanisms based on cuckoo search, Applied Soft Computing, volume 54, 2017, pp. 46 - 61. DOI: http://dx.doi.org/10.1016/j.asoc.2017.01.024
     
  11. Shima Javanmard, Behrouz Afshar-Nadjafi, Seyed Taghi Akhavan Niaki, Preemptive multi-skilled resource investment project scheduling problem: Mathematical modelling and solution approaches, Computers and Chemical Engineering 96 (2017) 55–68, DOI: dx.doi.org/10.1016/j.compchemeng.2016.11.001
     
  12. M. Fu, H. Wang, B. Fang and X. Huang, "Study on Agent-Updating Algorithms for Coalition Skill Games," 2016 9th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, 2016, pp. 112-117. DOI: 10.1109/ISCID.2016.2035
     
  13. Mohammad Rostami; Morteza Bagherpour; Mohammad Mahdavi Mazdeh; and Ahmad Makui, Resource Pool Location for Periodic Services in Decentralized Multi-Project Scheduling Problems Journal of Computing in Civil Engineering, 2017. http://ascelibrary.org/doi/full/10.1061/%28ASCE%29CP.1943-5487.0000671
     
  14. Hamidreza Maghsoudlou, Behrouz Afshar-Nadjafi, Seyed Taghi Akhavan Niaki, Solving a Multi-Objective Mathematical Model for a Multi-Skilled Project Scheduling Problem by CPLEX Solver Applied Soft Computing (accepted manuscript), online 17 January 2017 DOI http://dx.doi.org/10.1016/j.asoc.2017.01.024
     
  15. Reza Kia, Parisa Shahnazari-Shahrezaei, Sina Zabihi Solving a Multi-Objective Mathematical Model for a Multi-Skilled Project Scheduling Problem by CPLEX Solver Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on DOI 10.1109/IEEM.2016.7798072
     
  16. Aurelia Ciupe, Serban Meza, Bogdan Orza, Heuristic Optimization for the Resource Constrained Project Scheduling Problem: a Systematic Mapping Proceedings of the Federated Conference on Computer Science DOI: 10.15439/2016F389 and Information Systems pp. 619–626 ACSIS, Vol. 8. ISSN 2300-5963 DOI 10.15439/2016F389
     
  17. Taiba Zahid, Michael Völker, Thorsten Schmidt, Simulation of Extended Resource Constrained Scheduling Problem with a Soft Computed Priority Heuristic, Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, March 8-10, 2016, http://ieomsociety.org/ieom_2016/pdfs/355.pdf
     
  18. Mathias Kühn, Zhugen Zhou, Taiba Zahid, Oliver Rose, Michael Völker; Investigation of genetic operators and priority heuristics for simulation based optimization of Multi-Mode Resource Constrained Multi-Project Scheduling Problems (MMRCMPSP), Proceedings 30th European Conference on Modelling and Simulation ©ECMS Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose (Editors), 2016. DOI: http://dx.doi.org/10.7148/2016-0481
     
  19. Simona Corde, Viorica Rozina Chifu, Ioan Salomie, Emil St. Chifu, Andreea Iepure, Bird Mating Optimization Method for One-to-N Skill Matching, 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), Page(s):155 - 162, DOI 10.1109/ICCP.2016.7737139
     
  20. Shima Javanmard, Behrouz Afshar-Nadjafi, Seyed Taghi Akhavan Niaki, Preemptive multi-skilled resource investment project scheduling problem: Mathematical modelling and solution approaches, Computers and Chemical Engineering 96 (2017) 55–68 Article link
     
  21. Gergő Dori, Simulation-based methods for float time determination and schedule optimization for construction projects, PhD Thesis, Ingenieurfakultät Bau Geo Umwelt, Technische Universität München 2016 PDF
     
  22. Ciupe A., Orza B., Florea C., Vlaicu A., Skill-oriented priority scheduling for solving the Resource Constrained Project Scheduling Problem, in Intelligent Computer Communication and Processing (ICCP), 2015 IEEE International Conference on , vol., no., pp.85-92, 3-5 Sept. 2015 (doi: 10.1109/ICCP.2015.7312610)
     
  23. Xiaolong, Zheng; Ling, Wang; Huanyu, Zheng, "A knowledge-based fruit fly optimization algorithm for multi-skill resource-constrained project scheduling problem," in Control Conference (CCC), 2015 34th Chinese , vol., no., pp.2615-2620, 2015
     
  24. ZHANG Meng, LU Zhi-qiang, "Improved algorithm for the multi-skill resource constrained project scheduling problem", Computer Integrated Manfufacturing Systems Journal, May 2015.
     
  25. Pawinski, G.; Sapiecha, K., An Efficient Solution of the Resource Constrained Project Scheduling Problem Based, Recent Advances in Computational Optimization, 978-3-319-21132-9, 2016.
     
  26. Indu S. JAISWAR, Vinay B.HARSORA , REVIEW OF SCHEDULING AND OPTIMIZATIONTECHNIQUES, 4TH International Conference on Computer science and Information technology (ICCIT-2015), ISBN: 978-93-85225-08-6, 2015
     
  27. Huan-yu, Zheng and Ling, Wang and Xiao-long, Zheng, Teaching–learning-based Optimization algorithm for multi-skill resource constrained project scheduling problem, Soft Computing 2015.
     
  28. Asamaa Atef, Mohamed Abdel-Baset, Ibrahim El-henawy, Project Scheduling: Survey and Research Potentials, International Journal of Computer Applications Technology and Research (IJCAT), Vol.4-Issue 4, 235-241, 2015, ISSN: 2319 – 8656
     
  29. F.Zammori, M.Bertolini, A Conceptual Framework for Project Scheduling with Multi-skilled Resources, International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2015), 2015.
     
  30. M.H.Oladeinde, C.A.Oladeinde, A PERMUTATION ENCODING TECHNIQUE APPLIED TO GENETIC ALGORITHM SOLUTION OF RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM, Nigerian Journal of Technology (NIJOTECH), dx.doi.org/10.4314/njt.v34i1.1 http://dx.doi.org/10.4314/njt.v34i1.16 Vol. 34 No. 1, January 2015, pp. 127 – 132.
     
  31. Haseeba N., Sajeer k, A Survey on Software Project Scheduling Methods, IJCAT - International Journal of Computing and Technology, Volume 2, Issue 1, January 2015 ISSN : 2348 - 6090
     
  32. Haseeba N., Sajeer K., Ant Colony Optimization Algorithm for Software Project Scheduling Using Critical Chain Project Management, International Journal Of Engineering And Computer Science (IJECS) ISSN:2319-7242 Volume 4 Issue 7, 2015, Page No. 13332-13335
     
  33. Pawinski, G.; Sapiecha, K., "A Developmental Genetic Approach to the cost/time trade-off in Resource Constrained Project Scheduling," in Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on , vol., no., pp.171-179, 7-10 Sept. 2014
    Annals of Computer Science and Information Systems, vol.2, 2015, pp. 171--179.