Journal of Iranian Architecture & Urbanism(JIAU)

Abstract Extended Abstract
Background and Objectives: Today, due to the wide range of variables affecting architectural design, the computer is used as a tool in interaction with the design process to find optimal and high-performance solutions. It is necessary to investigate these methods due to their limitations and the complexity of space planning regarding the effective number of parameters. Improving the design quality and construction of architectural works is a common concern in developing countries, a step that can promote contemporary Iranian architecture. Furthermore, one of the design and construction characteristics in these developing countries is the tendency to improve the quality of architecture by using new technologies.
Methods: Space planning in architecture is one of the most practical and complex issues in architectural design and is considered one of the most challenging issues in recent research. The use of new technology-dependent methods in design, especially with an emphasis on using evolutionary algorithms as a solution, has been considered in the present research. Therefore, this study investigates the application and use of these algorithms as a solution for design optimization. The research questions of this study are:
- Concerning the application of optimization algorithms in space planning design, which algorithms have been used as basic or complementary algorithms? How frequently have the Swarm Intelligence Algorithms, especially particle swarm optimization algorithms, been used in this regard? 
- What are the possibilities and limitations in spatial organization design in architecture using genetic algorithms compared to the particle swarm optimization algorithm as the two main evolutionary algorithms?
- What is the implementation process and application of the particle swarm optimization algorithm in spatial organization design in architecture?
In order to answer the research questions, 35 types of research that have used optimization algorithms in architectural spatial planning design are collected. Then, the content analysis method was used to extract all the variables used in architectural plan optimization. In the same way, the basic algorithm and the complementary algorithms, if any, were extracted.
Based on the study of specific sources regarding the evolutionary optimization algorithm from the available bibliographic resources and the analysis of planning requirements and architectural space design, the genetic algorithm and swarm particle optimization algorithm were explained in designing the architectural spatial organization. The speed and quality of these two algorithms in investigating the research problem have been scrutinized based on software capacities in algorithm implementation and possibilities and limitations in using analytical methods for designing architectural plans. After explaining the objectives and numerical criteria, the particle swarm optimization algorithm using Microsoft Visual Studio programming software and .NET programming platform in C #, with WinodowsForm graphical user interface, was used to monitor the algorithm developing process and its results further.
Findings: This research introduces the features of metaheuristic algorithms and presents various optimization algorithms, including deterministic, heuristic, and metaheuristic algorithms. Also, the application of optimization algorithms in architecture is explained. The background of the evolutionary optimization algorithms and swarm particle optimization in the architectural plan design were also examined. After comparing the performance of the genetic algorithm and particle swarm optimization algorithm in optimizing the spatial organization, the swarm optimization algorithm structure was introduced. Finally, the application of this algorithm in plan design was studied and explained. Accordingly, plan design algorithms were classified into three stages: In the first stage, the goals, criteria, and constraints affecting the architectural spatial organization were determined, and they were classified into (1) The primary criteria and constraints, (2) The designers’ criteria and constraints, and (3) The contacts’ (client and users) criteria and constraints. In the numeric stage, the criteria of land boundary, list of spaces, permissible aspect ratios, permissible dimensions, total area, space interference, space adjacency, daylighting, and verification of the spaces were quantified. Then, the algorithm is determined based on the particle swarm optimization algorithm in two steps. Finally, the implementation platform of the algorithm is determined.
Conclusion: The difficulty of working with programming languages, software skills, and the software complexity due to inadequacy to combine various scientific fields has made using programming languages uncommon for designers to control the design parameters. This study compared the performance of two genetic algorithms and particle swarm optimization as the representatives of the two main groups of evolutionary algorithms in a base problem. It was shown that the particle swarm optimization algorithm converges faster and has a higher quality to optimize the plan regarding the parameters affecting the plan design. Implementation of an operational solution to optimize the spatial organization of the plan with emphasis on the affecting parameters in the formation of architectural plans was proposed in a three-step process using this algorithm. The problem objectives were examined in three related areas. The quantification process and the final model implementation were completed based on the particle swarm optimization algorithm in the .NET programming platform, along with a graphical interface as user interfaces for architects to understand the implementation process better. In addition to achieving optimal plans, future research interests in this field were also introduced. Regarding the specific entity of architecture, the existing computer software is insufficient for implementing the algorithm, providing visual and operational efficiency, and needs to be developed and customized for broader application in various fields of design.

Abstract Extended Abstract
Background and Objectives: Landscapes in general and townscapes in specific are susceptible to various natural and non-natural risks. Flooding is considered one of the primary factors that contribute to the vulnerability and problems faced by landscapes and townscapes. Although these conditions are present worldwide, they are more severe in Iran compared to other countries. On the one hand, natural disasters such as floods and earthquakes threaten this region. On the other hand, the built environments of this country are threatened by the weakness of inadequate building construction trends. In many cases, the structural systems and materials used in buildings do not meet the risk management requirements of the development process. The negative impact of the threatening development process has relatively different consequences on place dimensions. The impacts of disasters are often linked to the sensitivity of the specific features of a place. Among these features, townscapes and landscapes are particularly vulnerable to various disasters, more so than other dimensions of a place such as function and management. The future of a place is shaped by the consequences that occur in different zones and areas of communities. The measurement of vulnerability and resilience should consider the normative qualities of the environment, especially in terms of geographical contexts. The aim of this research is to assess the resilience of townscapes in relation to their environmental qualities, such as efficiency, richness, attraction, and variety, through the use of a case study approach. The research aims to assess the flood vulnerability of the Pole-Dokhtar region and city, with a particular emphasis on the spring 2019 flood. The study will use a case study approach and evaluate the resilience of the townscapes in relation to environmental qualities, such as efficiency, richness, attraction, and variety. The region of Pole-Dokhtar in Lorestan province, Iran, will be the specific area of focus.
Methods: The research method will involve the application of the development category to identify and address the major problems related to flood vulnerability. By this condition, the city engine analytical software has been used for analysis and finding trends of case study area data and information process. The research methodology involves three actions in field study techniques, which are the examination of current documents, site observation, and interviews with relevant stakeholders at the local and national levels. These studies incorporate data gathering stages. For data gathering trends, three sources have been used: 1- the information from the Pole-Dokhtar city’s master and detailed plans, as well as any written documents relating to any regional development plans and studies 2- Official data from 2019 flood variables. 3- Field survey, with emphasis on direct observation in the Pole-Dokhtar urban area. Observation trends encompass a journey to Lorestan province, Pole- Dokhtar County and Pole-Dokhtar city in spring 2020. In addition, the data has been analyzed through GIS and SPSS logic, techniques, and tools. Then, using the SWOT matrix helped researchers to compare the basic influential factors in terms of contextual strengths, weakness, threats, and opportunities.
Findings: The research has produced three main findings. Firstly, it highlights the vulnerability of areas like Pole-Dokhtar not only to floods but also to other natural and man-made disasters. Secondly, the research reveals the importance of specific attention to the land slope, river basin, and soil foundation to maintain environmental quality in urban landscapes. Lastly, the study emphasizes the need for a comprehensive examination of various planning documents at different levels, including master, structure, and detail plans.
Conclusion: In summary, the achievements of this study encompass various research outcomes regarding both townscape resilience and vulnerability of national, regional level and scale on various geographical contexts. In spite of this, long-term experiences in disasters like wars, earthquakes, droughts, floods and the same Iranian communities could not benefit from their valuable lessons. Learning from these valuable experiences should be the key lessons to solve and resolve ongoing problems and challenges which are essential for the comprehensive development of a country.