Seyyed Mohammad Mirhosseini

The successful completion of construction and industrial projects in the form of budget, time and quality and getting the satisfaction of the beneficiaries of the project is the ultimate goal of project management. The current research aimed to analyze the risk management model in construction projects with the approach of managing time and financial resources. In the qualitative part, firstly, by means of thematic analysis, by using interviews with experts, a theoretical framework and a conceptual model were developed, and its reliability and validity were determined by the Delphi method, and then, the structural model of risk management of construction projects with the approach of managing time and financial resources was determined. In management issues, there are things like "managers should have a written plan regarding the maintenance of human resources”, “at each stage of the work process, in order to optimally implement that process and also make businesses more profitable, managing the costs of that stage can be fruitful", "always during the process of implementing projects, issues and problems arise that require the ability of managers to solve those issues and make timely decisions in order to prevent multiple losses" showing the importance of management factors in construction projects.

Analyzing financial ratios over consecutive years is beneficial for evaluating the financial performance of construction companies. However, such an analysis can be tedious due to the vast number of the ratios. Therefore, developing an expert system based on artificial intelligence algorithms to identify and predict factors influencing the construction companies' financial performance is essential. To this end, a hybrid model based on Genetic Algorithm (GA) and Adaptive Neuro-Fuzzy Inference System (ANFIS) was introduced in this research to predict the financial performance of construction companies in Iran. This research is applied as descriptive and in terms of methodology well developed; also conducted cross-sectionally. The statistical population included all active construction companies in the construction sector in Tehran. Due to time and resource constraints, a random sampling technique was used. A questionnaire was utilized for data collection and data analysis, factor analysis methods and neuro-fuzzy system combined with GA were employed. The ANFIS combined with GA can evaluate the construction companies' financial performance with the minimum error. The findings ultimately resulted development of a model that forecasts the financial performance of Iranian construction companies, allowing them to concentrate on factors that improve financial performance.

Successful civil projects are one of the key factors in the economic development. Civil projects are always criticized for time and budget wastage. Delays in the execution of these projects sometimes not only waste national resources and cause social damages, but also may ultimately render the project economically unjustifiable, to the extent that the direct and indirect damages from delays can sometimes exceed the actual value of the project. However, despite all government efforts, projects in Iran still suffer from delays. Therefore, managing the delays in construction projects in Iran for optimal utilization and proper management is essential. This research proposes a delay management model for construction projects based on evaluating the effective factors on the delay of construction projects in Iran using system dynamics and optimization methods. Finally, a model suitable for the managerial situation in top-ranked contracting companies in Tehran province was presented. The validation and credibility assessment of the proposed model in managing the delay of construction projects in Iran indicated that, by combining these two approaches, project managers can improve project performance under dynamic system conditions. This innovation can be utilized in different industries, especially in the construction industry. In fact, this study provides an optimal response to the management of delays in construction projects by changing the planning horizon using integrated tracking methods and identifying the best strategy and planning horizon for policymakers. Through this, an optimal planning horizon for managing delays in construction projects in the real world is achieved.