@ARTICLE{Hosseini_S.A._Bilans_2017, author={Hosseini, S.A. and Akbarpour, A. and Ahmadi, H. and Aminnejad, B.}, number={No 4}, journal={Archives of Civil Engineering}, pages={103-121}, howpublished={online}, year={2017}, publisher={WARSAW UNIVERSITY OF TECHNOLOGY FACULTY OF CIVIL ENGINEERING and COMMITTEE FOR CIVIL ENGINEERING POLISH ACADEMY OF SCIENCES}, abstract={Underground spaces having features such as stability, resistance, and being undetected can play a key role in reducing vulnerability by relocating infrastructures and manpower. In recent years, the competitive business environment and limited resources have mostly focused on the importance of project management in order to achieve its objectives. In this research, in order to find the best balance among cost, time, and quality related to construction projects using reinforced concrete in underground structures, a multi-objective mathematical model is proposed. Several executive approaches have been considered for project activities and these approaches are analyzed via several factors. It is assumed that cost, time, and quality of activities in every defined approach can vary between compact and normal values, and the goal is to find the best execution for activities, achieving minimum cost and the maximum quality for the project. To solve the proposed multi-objective model, the genetic algorithm NSGA-II is used.}, type={Artykuły / Articles}, title={Bilans kosztów, czasu i jakości w odniesieniu do projektów budowlanych dotyczących betonu zbrojonego w konstrukcjach podziemnych z wykorzystaniem algorytmu meta-heurystycznego}, title={Balance of cost, time, and quality related to construction projects regarding the reinforced concrete of underground structures using a meta-heuristic algorithm}, URL={http://www.journals.pan.pl/Content/115482/PDF/103-121_ace-2017-0043.pdf}, keywords={konstrukcje podziemne, zarządzanie projektem, bilans kosztów, czasu i jakości, algorytm metaheurystyczny, algorytm genetyczny, Underground structures, Project management, Balance of cost, time and quality, Meta-Heuristic, Geneticalgorithm}, }