Multi-objective Optimization for Smart City Concepts: Smart Floating Cities (SFC)

Ayca Kirimtat

Doctoral thesis

Abstract:

Previous to the emersion of two premises “smart city” and “floating cities”, the population of manlike has been enhanced and land shortage has started to be realized by the humankind in the world. Consequently, the conception of intelligent city has been lengthened to the scholar epoch as an original outcome by investigators. Afterwards, the "floating city" conception has been adopted to the literature by a small number of researchers so as to make preparation for fighting with ascending sea levels. On the contrary, constructing an intelligent city is identified as a complicated layout planning amongst scientists, and designers, therefore multi-objective evolutionary optimization could be utilized to figure out this complex design problem by enhancing residents’ requirements. As a result of these statements, the outcomes of various evolutionary algorithms such as Self-adaptive Differential Evolution (jDE), Self-adaptive Continuous Genetic Algorithm with Differential Evolution (JcGA-DE), a nondominated sorting genetic algorithm (NSGAII), and a harmony search (MOHS) algorithm are compared by optimizing opposed objectives in three divergent case studies. In the preliminary case study, the objective functions namely as “visual comfort” and “accessibility” between the functions in the problem of smart floating city, are trying to be optimized. In the following and second design problem, the travelling distances are trying to be minimized while the cost efficiency is being maximized under the sea level. In the last case study, the maximization of natural light and the minimization of total energy consumption are targeted within the smart building. As a continuation of the dissertation, the consequences of the design problems through the Pareto front graphs of different algorithms are associated and discoursed.

Keywords

smart city, floating city, multi-objective optimization

Language used: English

Date on which the thesis was submitted / produced: 16. 8. 2021

Thesis defence

• Date of defence: 30. 8. 2021
• Supervisor: prof. Ing. Ondřej Krejcar, Ph.D.
• Reader: prof. RNDr. Peter Mikulecký, Ph.D., Martin Černý, Michal Munk

University of Hradec Králové

Faculty of Informatics and Management

Doctoral programme / field:
Aplikovaná informatika / Applied Informatics