The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Fuzzy Based Project Time-Cost Optimization Using Simulated Annealing Search Technique
Abstract
The Project time-cost optimization is inherently a complex task. Because of various kinds of uncertainties, such as weather, productivity level, inflation, human factors etc. during project execution process, time and cost of each activity may vary significantly. The complexity multiplies several folds when the operational times are not deterministic, rather fuzzy in nature. Therefore, deterministic models for time-cost optimization are not yet efficient. It is very difficult to find the exact solution of savings in both time and cost. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, this paper develops a simple approach with Simulated Annealing (SA) based searching technique. The proposed model leads the decision makers to choose the desired solution under different values of a-cut. Finally, taking a real project, the performance of SA has been tested.
Related Content
|
Fani Antoniou, Marina Marinelli, Kleopatra Petroutsatou.
© 2024.
31 pages.
|
|
Konstantinos Kirytopoulos, Vasileios Sarlis, Dimitris Marinakis, Theodoros Kalogeropoulos.
© 2024.
26 pages.
|
|
Konstantina Ragazou, Ioannis Passas, Alexandros Garefalakis, Constantin Zopounidis.
© 2024.
24 pages.
|
|
Vannie Naidoo, Rajen Chetty.
© 2024.
19 pages.
|
|
Alexandros E. Grigoras, Georgios N. Aretoulis, Fani Antoniou, Stylianos Karatzas.
© 2024.
30 pages.
|
|
Kleopatra Petroutsatou, Theodora Vagdatli, Marina Chronaki, Panagiota Samouilidou.
© 2024.
24 pages.
|
|
Dimitra Korakaki, Stratos Kartsonakis, Evangelos Grigoroudis, Constantin Zopounidis.
© 2024.
34 pages.
|
|
|