| Title |
Evolutionary Computation for the Development of Smart Floating Cities |
| ID_Doc |
44287 |
| Authors |
Kirimtat, A; Krejcar, O; Tasgetiren, MF |
| Title |
Evolutionary Computation for the Development of Smart Floating Cities |
| Year |
2020 |
| Published |
|
| DOI |
10.1109/ICIT45562.2020.9067105 |
| Abstract |
Prior to the emergence of both terms "smart city" and "floating cities", the human population has already increased and land scarcity has begun to be grasped by the humanity across the world. Therefore, as a first challenge, the concept of smart city has been extended to the scientific era as a novel solution by researchers. Thereafter, the floating city concept has been introduced in the literature by a couple of scientists in order to make provision against rising sea levels. On the other hand, designing a city is known as a complex design problem among engineers, architects and designers, thus evolutionary algorithms could be used to solve this complicated problem by optimizing inhabitants' demands. We, in this research, compare the results of two different evolutionary algorithms namely as Self-adaptive Differential Evolution (DE) and Self Adaptive Continuous Genetic Algorithm with Differential Evolution (DE) by optimizing two conflicted objective functions visual comfort and accessibility between the nodes in the proposed smart floating city. |
| Author Keywords |
evolutionary algorithms; floating cities; smart cities; multi-objective optimization |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000560681600125 |
| WoS Category |
Engineering, Electrical & Electronic |
| Research Area |
Engineering |
| PDF |
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