A multi-objective optimization model for urban planning: The case of a very large floating structure. (January 2019)

• Record Type: Journal Article
• Authors: Levi, Yedidya; Bekhor, Shlomo; Rosenfeld, Yehiel
• Is Part Of: Transportation research. Volume 98(2019)
• Page Start: 85
• Page End: 100
• Publication Date: 2019-01
• Subjects: Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2018.11.013
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Optimization model of an artificial island composed of Very Large Floating Structures (VLFSs). Bi-level optimization problem formulation including floating module constraints. A modified genetic algorithm is developed to find the Pareto front in a reasonable amount of time. A test case illustrates the feasibility of the proposed planning method. Abstract: 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.