Abstract
Recent techniques in multi-mode project scheduling and multiobjective optimization with Evolutionary Algorithms are combined in this paper. We propose a single step Evolutionary Algorithm to find multiple Pareto-optimal solutions to the multi-mode resource-constrained project scheduling problem which make it possible that the decision maker can be able to choose the most appropiate solution according to the current decision environment.
Keywords
- Multiobjective Optimization
- Renewable Resource
- Project Schedule
- Nonrenewable Resource
- Project Schedule Problem
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
The author thanks the Instituto de Fomento de la Region de Murcia for its financing through the Seneca Program.
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© 1999 Springer-Verlag Berlin Heidelberg
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Gómez-Skarmeta, A.F., Jiménez, F., Ibáñez, J. (1999). Pareto-optimality in Scheduling Problems. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_21
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DOI: https://doi.org/10.1007/3-540-48774-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
Online ISBN: 978-3-540-48774-6
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