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Optymalizacja procesów budowlanych - algorytmy genetyczne

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Warianty tytułu
EN
Optimisation of building engineering processes - genetic algorithms
Języki publikacji
PL
Abstrakty
EN
Building process is defined as a sequence of activities, that have a differentiated character - administrative, legal, technological etc. Between activities in construction process existence cause-effect relationship. However basic criterions decisive about building process estimation focus on cost and time. This article trays to evaluate new optimization method - genetic algorithm, that is a sat of tool based on natural selection and the mechanism of population genetics. Aim of this paper is to demonstrate the use of genetic algorithm system in time-cost optimization problems in construction planning. This article indicates, that this optimization process proceed efficiently and optimal solution can be obtained quickly.
Słowa kluczowe
Rocznik
Strony
35--45
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
autor
Bibliografia
  • [1] J. Arabas, Wykłady z algorytmów ewolucyjnych, WNT, Warszawa 2001.
  • [2] D. Bargieł, Implementacja algorytmu genetycznego w C++, Software 2,0 02/2002, s. 40-45.
  • [3] W. Chan, D. Chua, G. Kannan, Construction resource scheduling with genetic algorithms, Journal of Construction Engineering and Management, ASCE 122(2), 1996, s. 125-132.
  • [4] H.N. Chiu, M.T. Tsai, An efficient search procedure for the resource-constrained multi project scheduling problem with discounted cash flows, Construction Management and Economics 2002 (20), s. 55-66.
  • [5] C. Feng, L. Liu, S.A. Burns, Using genetic algorithms to solve construction time-cost trade-off problems, Journal of Computing in Civil Engineering, ASCE 11(3), 1997, s. 184-189.
  • [6] D. Goldberg, Algorytmy genetyczne i ich zastosowania, WNT, Warszawa 1995.
  • [7] T. Hegazy, N. Wassef, Cost optimization in projects with repetitive nonserial activities, Jurnal of Construction Engineering and Management, ASCE 127(3), 2001, s. 183-191.
  • [8] P. Josephson, B. Larsson, H. Li, Illustrative benchmarking rework and rework cost in Swedish construction industry, Journal of Management in Engineering, ASCE 18(3), 2002, s. 76-82.
  • [9] P. Koprzycki, Algorytmy genetyczne - elementy składowe, Software 2,0 02/2001, s. 32-37.
  • [10] S. Leu, T. Hung, A genetic algorithm-based optimal resource-constrained scheduling simulation model, Construction Management and Economics 2002 (20), s. 131-141.
  • [11] H. Li, P. Love, Using improved genetic algorithms to facilitate time-cost optimization, Journal of Construction Engineering and Management, ASCE 123(3), 1997, s. 233-237.
  • [12] P. Love, Influence of project type and procurement method on rework cost in building construction projects, Journal of Construction Engineering and Management, ASCE 128(1), 2002, s. 18-28.
  • [13] Z. Michalewicz, Algorytmy genetyczne + struktury danych = programy ewolucyjne, WNT, Warszawa 1999.
  • [14] B. Que, Incorporating practicability into genetic algorithm-based time-cost optimization, Journal of Construction Engineering and Management, ASCE 128(2), 2002, s. 139-143.
  • [15] R. Schaefer, Podstawy genetycznej optymalizacji globalnej, Wydawnictwo Uniwersytetu Jagiellońskiego, Kraków 2002.
  • [16] J.J. Shi, S.O. Cheung, D. Arditi, Construction delay computation method, Journal of Construction Engineering and Management, ASCE 127(1), 2001, s. 60-65.
  • [17] C.M. Tam, T. Tong, S.O. Cheung, Genetic algorithm model in optimizing the use of labour, Construction Management and Economics 2001(19), s. 207-215.
  • [18] T. Tong, C.M. Tam, A. Chan, Genetic algorithm optimization in building port-folio management, Construction Management and Economics 2001(19), s. 601-609.
  • [19] S. Ye, R. Tiong, NPV-at-Risk method in infrastructure project investment evaluation, Journal of Construction Engineering and Management, ASCE 126(3), 2000, s. 227-233.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BGPK-0379-2588
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