Model to Optimize the Management of Strategic Projects Using Genetic Algorithms in a Public Organization

被引:1
|
作者
Izurieta, Richard Romero [1 ,2 ]
Toapanta Toapanta, Segundo Moises [3 ]
Caucha Morales, Luis Jhony [2 ]
Bano Hifong, Maria Mercedes [3 ]
Gomez Diaz, Eriannys Zharayth [4 ]
Mafla Gallegos, Luis Enrique [5 ]
Maciel Arellano, Ma Rocio [6 ]
Orizaga Trejo, Jose Antonio [6 ]
机构
[1] Univ Estatal Milagro UNEMI, Fac Educ Sci, Milagro 091051, Ecuador
[2] Univ Nacl Tumbes, Postgrad Sch, Tumbes 24001, Peru
[3] Univ Catolica Santiago Guayaquil UCSG, Postgrad Subsyst, Guayaquil 090615, Ecuador
[4] Inst Tecnol Super Ruminahui, Res Dept, Sangolqui 171103, Ecuador
[5] Escuela Politecn Nacl EPN, Fac Engn Syst, Quito 170525, Ecuador
[6] Univ Guadalajara, Informat Syst Dept CUCEA, Guadalajara 44100, Jalisco, Mexico
关键词
BPNN; multi-objective optimization; genetic algorithm; information security; mathematical model; NSGA-II; INFORMATION SECURITY; NSGA-II; PORTFOLIO; RISK; UNCERTAINTY; GOVERNANCE;
D O I
10.3390/info13110533
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Public organizations lack adequate models and methods to efficiently support and manage processes related to information security and IT investments. The objective is to optimize the management of strategic projects planned to improve the information security of a public organization and make efficient use of its available resources. The deductive method and exploratory research were used to review and analyze the available information. A mathematical model resulted that optimizes two objectives: (1) minimizing the costs of the strategic projects to be executed, and (2) maximizing the percentage of improvement in the organization's information security. According to the result of the simulation, a subset of planned strategic projects was obtained that allows improving the information security of a public organization from 84.64% to 92.20%, considering the budgetary limitations of the organization. It was concluded that the proposed model is efficient, practical and can be a support tool for the IT management of a public organization.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Using Genetic Algorithms to Optimize Redundant Data
    Szulc, Iwona
    Stencel, Krzysztof
    Wisniewski, Piotr
    BEYOND DATABASES, ARCHITECTURES AND STRUCTURES: TOWARDS EFFICIENT SOLUTIONS FOR DATA ANALYSIS AND KNOWLEDGE REPRESENTATION, 2017, 716 : 165 - 176
  • [2] Prototype to Optimize the Management of Information Security Used by Internal Users in a Public Organization of Ecuador
    Toapanta Toapanta, Segundo Moises
    Castro De La Rosa, Francisco Xavier
    Navarrete Fernandez, Eduardo Michael
    Trivino Trivino, Fabrizio Dario
    Mafla Gallegos, Luis Enrique
    PROCEEDING OF THE 2019 INTERNATIONAL CONFERENCE ON COMPUTER, INFORMATION AND TELECOMMUNICATION SYSTEMS (IEEE CITS 2019), 2019, : 71 - 75
  • [3] Using a genetic algorithm to optimize an expert credit rating model
    Estran, Remy
    Souchaud, Antoine
    Abitbol, David
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 203
  • [4] Research on using genetic algorithms to optimize Elman neural networks
    Ding, Shifei
    Zhang, Yanan
    Chen, Jinrong
    Jia, Weikuan
    NEURAL COMPUTING & APPLICATIONS, 2013, 23 (02): : 293 - 297
  • [5] Research on using genetic algorithms to optimize Elman neural networks
    Shifei Ding
    Yanan Zhang
    Jinrong Chen
    Weikuan Jia
    Neural Computing and Applications, 2013, 23 : 293 - 297
  • [6] A Strategic Service Management Model in National Gas Distribution Projects
    Esmaeilzadeh, Fereidoun
    Askarifar, Kazem
    Alamdari, Pegah
    TEHNICKI GLASNIK-TECHNICAL JOURNAL, 2020, 14 (04): : 416 - 422
  • [7] Scheduling of Multiple Projects with Resource Constraints Using Genetic Algorithms
    Qiao, L. H.
    Wang, C.
    MANUFACTURING AUTOMATION TECHNOLOGY, 2009, 392-394 : 755 - 760
  • [8] The optimization of success probability for software projects using genetic algorithms
    Reyes, Francisco
    Cerpa, Narciso
    Candia-Vejar, Alfredo
    Bardeen, Matthew
    JOURNAL OF SYSTEMS AND SOFTWARE, 2011, 84 (05) : 775 - 785
  • [9] Optimising Forest Management Using Multi-Objective Genetic Algorithms
    Castro, Isabel
    Salas-Gonzalez, Raul
    Fidalgo, Beatriz
    Farinha, Jose Torres
    Mendes, Mateus
    SUSTAINABILITY, 2024, 16 (23)
  • [10] Using genetic algorithms to optimise model parameters
    Wang, QJ
    ENVIRONMENTAL MODELLING & SOFTWARE, 1997, 12 (01) : 27 - 34