Novel heuristic solutions for Multi-Skill Resource-Constrained Project Scheduling Problem

被引:0
|
作者
Myszkowski, Pawel B. [1 ]
Skowronski, Marek E. [1 ]
Podlodowski, Lukasz [1 ]
机构
[1] Wroclaw Univ Technol, Fac Comp Sci & Management, Inst Informat, Dept Artificial Intelligence, PL-50370 Wroclaw, Poland
关键词
GENETIC ALGORITHM;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article some novel scheduling heuristics for Multi Skill Resource Constrained Project Scheduling Problem have been proposed and compared to state-of-the-art priority rules, based on task duration, resource salaries and precedence relations. New heuristics stand an aggregation of known methods, but are enhanced by skills domain. The goal of the paper is to investigate, whether evaluated methods can be used as robustness enhancement tools in metaheuristics, mostly evolutionary algorithms. Experiments have been performed using artificially created dataset instances, based on real world instances. Obtained results prove that such methods stand interesting feature that can be included to more complex methods and increase their robustness.
引用
收藏
页码:159 / 166
页数:8
相关论文
共 50 条
  • [41] An Improved Tabu Search for Multi-skill Resource-Constrained Project Scheduling Problems Under Step-Deterioration
    Huafeng Dai
    Wenming Cheng
    Peng Guo
    [J]. Arabian Journal for Science and Engineering, 2018, 43 : 3279 - 3290
  • [42] Heuristic and metaheuristic methods for the multi-skill project scheduling problem with partial preemption
    Polo-Mejia, Oliver
    Artigues, Christian
    Lopez, Pierre
    Monch, Lars
    Basini, Virginie
    [J]. INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2023, 30 (02) : 858 - 891
  • [43] Preemptive multi-skill resource-constrained project scheduling of marine power equipment maintenance tasks1
    Wang, Peng
    Lu, Shaojun
    Cheng, Hao
    Liu, Lin
    Pei, Feng
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 44 (03) : 5275 - 5294
  • [44] Efficient selection operators in NSGA-II for Solving Bi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem
    Myszkowski, Pawel B.
    Laszczyk, Maciej
    Lichodij, Joanna
    [J]. PROCEEDINGS OF THE 2017 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 2017, : 83 - 86
  • [45] Teaching–learning-based optimization algorithm for multi-skill resource constrained project scheduling problem
    Huan-yu Zheng
    Ling Wang
    Xiao-long Zheng
    [J]. Soft Computing, 2017, 21 : 1537 - 1548
  • [46] A discrete oppositional multi-verse optimization algorithm for multi-skill resource constrained project scheduling problem
    Zhu, Lei
    Lin, Jian
    Wang, Zhou-Jing
    [J]. APPLIED SOFT COMPUTING, 2019, 85
  • [47] Heuristic Optimization for Robust Resource-Constrained Flexible Project Scheduling Problem
    Liu, Yongli
    Li, Renjie
    Liu, Huiran
    [J]. IEEE ACCESS, 2020, 8 : 142269 - 142281
  • [48] Teaching-learning-based optimization algorithm for multi-skill resource constrained project scheduling problem
    Zheng, Huan-yu
    Wang, Ling
    Zheng, Xiao-long
    [J]. SOFT COMPUTING, 2017, 21 (06) : 1537 - 1548
  • [49] Investigation of benchmark dataset for many-objective Multi-Skill Resource Constrained Project Scheduling Problem
    Myszkowski, Pawel B.
    Laszczyk, Maciej
    [J]. APPLIED SOFT COMPUTING, 2022, 127
  • [50] Resource-constrained project scheduling: a heuristic for the multi-mode case
    Heilmann, R
    [J]. OR SPEKTRUM, 2001, 23 (03) : 335 - 357