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Intelligent Engineering Systems through Artificial Neural Networks Volume 18
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ISBN-10:
0791802823
ISBN:
9780791802823
No. of Pages:
700
Publisher:
ASME Press
Publication date:
2008
eBook Chapter
51 Random Key-Based Genetic Algorithm for Solving Resource Constrained Project Scheduling Problem with Multiple Modes
By
Ikutaro Okada
School of Humanity-Oriented Science and Engineering, Kinki University ; iokada@fuk.kindai.ac.jp
,
Ikutaro Okada
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Mitsuo Gen
Graduate School of Information, Production & Systems, Waseda University ; gen@waseda.jp
,
Mitsuo Gen
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Seren Ozmehmet Tasan
Graduate School of Information, Poduction & Systems, Waseda University ; seren@akane.waseda.jp
Seren Ozmehmet Tasan
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Page Count:
8
-
Published:2008
Citation
Okada, I, Gen, M, & Tasan, SO. "Random Key-Based Genetic Algorithm for Solving Resource Constrained Project Scheduling Problem with Multiple Modes." Intelligent Engineering Systems through Artificial Neural Networks Volume 18. Ed. Dagli, CH. ASME Press, 2008.
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In the practice of scheduling of construction projects, there is a great variety of methods and procedures that need to be selected at each construction process during project. Accordingly, it is important to consider the different modes that may be selected for an activity in the scheduling of construction projects. In this study, first, we mathematically formulated the resource-constrained project scheduling problem with multiple modes while minimizing the total project time as the objective function. Following, we proposed a new random key-based genetic algorithm with fuzzy logic controller to solve this NP-hard optimization problem which has not been experimented before....
Topics:
Genetic algorithms
Abstract
1. Introduction
2. Resource-Constrained Project Scheduling Model with Multiple Modes
3. Random Key-Based Genetic Algorithm with Fuzzy Logic Controller
4. Computational Experiments
5. Conclusions
Reference
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