چكيده به لاتين
Construction companies are required to employ effective methods of project planning and scheduling in today's competitive environment. Time and cost are critical factors in project success, and they can vary based on the type and amount of resources used for activities, such as labor, tools, and materials. In addition, resource leveling strategies that are used to limit fluctuations in a project's resource consumption also affect project time and cost. In light of the significant increase of stakeholders in construction projects in recent years, pursuing other project goals, such as environmental impact, safety risks, and quality, would be prudent in the planning phase. The multi-mode resource-constrained discrete-time–cost-resource optimization (MRC-DTCRO) is an optimization tool that is developed for scheduling of a set of activities involving multiple execution modes with the aim of minimizing time, cost, and resource moment. Moreover, uncertainty in cost should be accounted for in project planning because activities are exposed to risks that can cause delays and budget overruns. In this study a fuzzy-multi-mode resource-constrained discrete-time–cost-resource optimization (F-MRC-DTCRO) model for the time-cost-resource moment tradeoff in a fuzzy environment while satisfying all the project constraints is presented. n the proposed model, fuzzy numbers are used to characterize the uncertainty of direct cost of activities. Using this model, different risk acceptance levels of the decision maker can be addressed in the optimization process. A newly developed multi-objective optimization algorithm called ENSCBO is used to search non-dominated solutions to the fuzzy multi-objective model. Moreover, a many-objective optimization model regarding time, cost, resource, environmental impact, safety, and quality based on a newly developed many-objective optimization algorithm, Non-dominated Sorting Differential Evolution algorithm based on Reference points (NSDE-R) is presented in this study. The proposed models' applicability is demonstrated employing case studies of construction projects. In this study, a framework is developed for making trade-offs among resources in project scheduling that integrates building information modeling (BIM), multi-objective optimization (MOO), and multi-criteria decision-making (MCDM). Using BIM construction management software, a 3D model is first created. Based on the model, a bill of quantities is generated for the project. Then, newly developed optimization algorithms are used to provide the optimal solution set.
