Implementation of multi-objective genetic algorithms for optimization of site layout planning : TOKİ Ayazma and Şahinbey cases

Abstract

Design decisions taken in the early stages of design play an important role in economizing energy consumption in residential buildings. The placement of blocks in site layout planning is one of these factors to reduce energy consumption. There are several criteria for the blocks settlement in site layout planning in residential buildings. In this study, two parameters were selected for placement of blocks in site layout planning. The first one is solar radiation which plays an important role in electric lighting savings and heating inside buildings during the winter semester. The latter one is the shadow which affects solar access for buildings. In the scope of this study, an optimization abilities of Genetic Algorithm are applied for solving site layout planning problems in the early stage designs. In the second chapter, Genetic Algorithm based design optimization approaches in site layout planning are examined under a four-fold taxonomy in this study; (1) change in time; (2) shape representation; (3) dimension of shape; (4) site layout. Later on, examples are given for studies of Genetic Algorithms in site layout planning by mentıoned factors. In the third chapter, Genetic Algorithms have been reviewed as a method for solving optimization problems in various fields of science. In the fourth chapter, an experiment model is defined for two Genetic Algorithm optimization methods such as single-objective and multi-objective in Rhinoceros/Grasshopper CAD modeling environment. The main purpose of this thesis is to maximize solar radiation and minimize shadow areas on vertical surfaces of blocks.