Abstract
In this paper, the design of systems using mechanical or electrical energy-transformation devices is treated as a knapsack problem. Due to the well-known NP-hard complexity of the knapsack problem, a combination of integer linear programming and evolutionary multi-criteria optimization is presented to solve this real problem with promising experimental results.
Keywords
- Integer Linear Programming
- Real Problem
- Knapsack Problem
- Total Input
- Pareto Frontier
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.
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Mallor-Gímenez, F., Blanco, R., Azcárate, C. (2007). Combining Linear Programming and Multiobjective Evolutionary Computation for Solving a Type of Stochastic Knapsack Problem. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds) Evolutionary Multi-Criterion Optimization. EMO 2007. Lecture Notes in Computer Science, vol 4403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70928-2_41
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DOI: https://doi.org/10.1007/978-3-540-70928-2_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70927-5
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