Multi-objective Parking Optimization
Multi-Objective Parking Optimization is a computational framework in transportation planning that simultaneously optimizes multiple conflicting objectives—such as minimizing walking distance, maximizing space utilization, and reducing search time—within parking allocation systems, distinguishing itself from single-objective approaches by integrating trade-off analysis and Pareto efficiency into decision-making processes.
14
Publications
767
Citations
53
Authors
27
Institutions
Publications per year
2017–2026
10
Parents
14
Reinforcement Learning-Based Motion Planning for Automatic Parking System
Jiren Zhang, Hui Chen, Shaoyu Song et al. · IEEE Access · 2020 · 74 citations · Full text
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Tongji University
Shanghai, China
2 h-index
8 publications
536 citations
University of Bonab
Bonāb, Iran
2 h-index
2 publications
65 citations

Tarbiat Modares University
Tehran, Iran
1 h-index
4 publications
832 citations
University of Hertfordshire
Hatfield, United Kingdom
1 h-index
1 publications
15 citations

Polytechnic University of Bari
Bari, Italy
1 h-index
4 publications
88 citations
Naval Academy
Istanbul, Turkey
1 h-index
1 publications
71 citations

Universidad Politécnica de Madrid
Madrid, Spain
1 h-index
2 publications
64 citations
Technical University of Munich
Munich, Germany
1 h-index
2 publications
120 citations
1–8 of 27
2 publications · 89 citations
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1 publications · 24 citations
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1 publications · 22 citations
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1 publications · 20 citations
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1 publications · 32 citations
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