A Multi-Objective Harmony Search Algorithm for Sustainable Design of Floating Settlements

Cemre Çubukçuoglu, Ioannis Chatzikonstantinou, Mehmet Fatih Tasgetiren, Sevil Sariyildiz, Quan-Ke Pan

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This paper is concerned with the application of computational intelligence techniques to the conceptual design and development of a large-scale floating settlement. The settlement in question is a design for the area of Urla, which is a rural touristic region located on the west coast of Turkey, near the metropolis of Izmir. The problem at hand includes both engineering and architectural aspects
that need to be addressed in a comprehensive manner. We thus adapt the view as a multi-objective constrained real-parameter optimization problem. Specifically, we consider three objectives, which are conflicting. The first one aims at maximizing accessibility of urban functions such as housing and
public spaces, as well as special functions, such as a marina for yachts and a yacht club. The second one aims at ensuring the wind protection of the general areas of the settlement, by adequately placing them in between neighboring land masses. The third one aims at maximizing visibility of the settlement from external observation points, so as to maximize the exposure of the settlement.
To address this complex multi-objective optimization problem and identify lucrative alternative design solutions, a multi-objective harmony search algorithm (MOHS) is developed and applied in this paper. When compared to the Differential Evolution algorithm developed for the problem in the literature, we demonstrate that MOHS achieves competitive or slightly better performance in
terms of hyper volume calculation, and gives promising results when the Pareto front approximation is examined.
Original languageEnglish
Article number51
Number of pages17
Issue number3
Publication statusPublished - 2016


  • evolutionary computation
  • harmony search algorithm
  • computational design
  • floating city optimization
  • performance based design
  • multi objective optimization


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