A dimensionality reduction approach for many-objective Markov Decision Processes: Application to a water reservoir operation problem |
| |
Affiliation: | 1. Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza L. da Vinci, 32, I-20133 Milano, Italy;2. Institute of Environmental Engineering, ETH Zurich, Stefano-Franscini-Platz 5, CH-8093 Zurich, Switzerland;1. Department of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA;2. Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;3. Center on Financial Risk in Environmental Systems, Gillings School of Global Public Health, UNC Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA |
| |
Abstract: | The operation of complex environmental systems usually accounts for multiple, conflicting objectives, whose presence imposes to explicitly consider the preference structure of the parties involved. Multi-objective Markov Decision Processes are a useful mathematical framework for the resolution of such sequential, decision-making problems. However, the computational requirements of the available optimization techniques limit their application to problems involving few objectives. In real-world applications it is therefore common practice to select few, representative objectives with respect to which the problem is solved. This paper proposes a dimensionality reduction approach, based on the Non-negative Principal Component Analysis (NPCA), to aggregate the original objectives into a reduced number of principal components, with respect to which the optimization problem is solved. The approach is evaluated on the daily operation of a multi-purpose water reservoir (Tono Dam, Japan) with 10 operating objectives, and compared against a 5-objectives formulation of the same problem. Results show that the NPCA-based approach provides a better representation of the Pareto front, especially in terms of consistency and solution diversity. |
| |
Keywords: | Many-objective optimization Markov Decision Processes Non-negative Principal Component Analysis Visual analytics Water resources management |
本文献已被 ScienceDirect 等数据库收录! |
|