A multi-objective optimization model for urban planning: The case of a very large floating structure
Autor: | Yehiel Rosenfeld, Yedidya Levi, Shlomo Bekhor |
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Rok vydání: | 2019 |
Předmět: |
050210 logistics & transportation
Mathematical optimization Optimization problem Computer science 05 social sciences Transportation Geometric shape 010501 environmental sciences Flow network 01 natural sciences Multi-objective optimization Computer Science Applications Task (project management) Urban planning 0502 economics and business Automotive Engineering Genetic algorithm 0105 earth and related environmental sciences Civil and Structural Engineering Very large floating structure |
Zdroj: | Transportation Research Part C: Emerging Technologies. 98:85-100 |
ISSN: | 0968-090X |
DOI: | 10.1016/j.trc.2018.11.013 |
Popis: | This paper develops an optimization model for planning an artificial island composed of Very Large Floating Structures (VLFSs). The optimization model addresses the geometric shape of the island (the array of floating platforms), the land-use layout, and the transportation network. The model developed in this paper considers the specific properties related to an artificial island made of multiple floating modules. The model is formulated as a bi-level optimization problem. In the upper level problem, the decision-maker is required to decide the land-use layout and the road network structure. The user behavior pattern is obtained by solving the lower level problem, which is dependent on the decisions taken at the upper level. Given the complexity of the problem, the paper develops modifications to the genetic algorithm to find the Pareto front in a reasonable amount of time. A test case illustrates the feasibility of the proposed planning method. The transportation model execution is the most time-consuming task, which highlights the need to prune irrelevant scenarios. The Pareto front shows a substitution pattern between different land-use configurations, in accordance with the different objective functions. |
Databáze: | OpenAIRE |
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