Multiple objective dynamic programming with forward filtering |
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| Affiliation: | 1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, China;2. School of Automation and Electrical Engineering, University of Science and Technology Beijing, China;3. Advanced Vehicle Engineering Center, Cranfield University, United Kingdom;1. Department of Mechanical Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7;2. School of Engineering, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada N1G 2W1;1. School of Automation, Beijing Information Science and Technology University, Beijing 100192, China;2. Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore;3. School of Cyber Science and Technology, Beihang University, Beijing 100191, China;4. Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310023, China;5. School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China |
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| Abstract: | In this paper we present a heuristic method for reducing the computational burden in multiple objective dynamic programming (MODP). Using techniques originally suggested for multiple objective linear programming, the solution set for each state (stage) are filtered, giving a representative subset of the set of efficient ways of attaining that state (stage). The method allows for considerable reductions in the amount of storage required to solve the problem, and in the dimensionality of the problem in solution space. It does not guarantee that all the identified solutions are non-dominated; however, the examples presented suggest that the representation of the subset of all efficient solutions is a good one. |
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