TY - JOUR
ID - 3935
TI - A Hybrid Genetic Algorithm to Maximize Net Present Value of Project Cash Flows in Resource Constrained Project Scheduling Problem with fuzzy parameters
JO - Scientia Iranica
JA - SCI
LA - en
SN - 1026-3098
AU - Fathallahi, Fatemeh
AU - Najafi, Amir Abbas
AD - Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran
Y1 - 2016
PY - 2016
VL - 23
IS - 4
SP - 1893
EP - 1903
KW - Discounted Cash Flows
KW - Net Present Value
KW - Fuzzy sets
KW - uncertainty
KW - genetic algorithms
DO - 10.24200/sci.2016.3935
N2 - This paper studies a specific resource constrained project scheduling problem under uncertainty. To do so, the problem is investigated in fuzzy environment and the goal is to maximize the net present value of the project cash flows. The problem is first mathematically formulated. Then, a hybrid Genetic Algorithm is proposed and tuned to solve this NP-hard problem. The performance of the proposed algorithm is evaluated with comparing two well-known metaheuristic algorithms through a set of instances. Finally, comprehensive computational results are illustrated and the results are analyzed and discussed.
UR - https://scientiairanica.sharif.edu/article_3935.html
L1 - https://scientiairanica.sharif.edu/article_3935_11a2efdc6248fd20edd5a326c183a48d.pdf
ER -