الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
In this thesis, a multiobjective optimization model for construction cash flow was illustrated. First of all, indispensable background facts and figures for cash flow issues and fundamental knowledge about the obstacle were surveyed. This incorporates project cost estimating, cash flow, material procurement and financial alternatives. Previous research attempts for solving various cash flow conflicts were also analyzed. Further and even more importantly, a brief of Genetic Algorithms optimization procedure was outlined and multiobjective optimization was also demonstrated. A cash flow optimization model was progressed. This research endeavors to improve financial declaration and cash flow by evolution of two models, first for material procurement and second for ameliorating financial alternatives and integrating the prior two models. The model employs the artificial intelligence techniques for optimization and is upholding by non-sorting genetic algorithm (NSGA) theory as a multiobjective sorting scheme. The Pareto front sorting concept was applied to evaluate the outcomes considering all objectives. In order to simplify the implementation of the proposed model, an automated system is approaching. MS-Excel was exercised as a result of its simplicity in application and programmability features. The automated system facilitates various optimization options via diverse commands, cash flow, material procurement plans, financial alternatives, and optimization. In order to recognize the fulfillment of the advanced model, two real-life construction projects were examined. The first case study is the ”City Stars El-Sahel” located in the North Coast, Egypt. The second case study is ”Hyde Park Compound” located in the New Cairo, Egypt. In both case studies, the model generated various optimal solutions (material procurement plans and financial alternatives), each characterized by one or more preferences over others. The two case studies confirm that the proposed model is adequate in modeling real-life construction projects and gives substantial results for project managers.