چكيده به لاتين
Planning for the material ordering during the providing schedule of project activities is a necessary requirement. However, in the traditional planning approach, firstly, the appropriate scheduling is determined and in the next step, the material ordering is planned with regard to the basic schedule of the previous step. This approach disregards the tradeoff between the project costs such as tardiness (earliness) costs and the material ordering costs such as ordering, holding and purchasing costs. On the other hand, modern organizations, in addition to focusing on economic dimensions, are also required to increase environmental and social functions in order to globalize. Because of their sustainability goals, they can establish an intra-generational and intergenerational justice, and surpass their rivals in the marketplace. In this research, a framework for project scheduling and material ordering with sustainability considerations has been proposed. In this framework, in the initial phase, all the resources and materials required for the project are identified and the potential suppliers are recognized accordingly. Also, after extracting sub-criteria and effective factors, environmental and social scores of suppliers have been determined by using Fuzzy Inference System. In the second phase, a multi-objective optimization model has been constructed and solved. This model is able to maximize the Net Present Value (NPV) of the project, the environmental score of suppliers and their social privilege simultaneously, so that the starting time of project activities, the time of ordering materials, the order quantity, and the proper suppliers are determined. Since the proposed model belongs to the class of NP-Hard problems, two multi-objective metaheuristic algorithms, MOPSO and NSGA-II, are proposed to solve the intended model. By solving 2700 standard problems in the Project Scheduling Problem Library (PSPBIB) and Using five criteria for evaluating the results of multi-objective solution methods, the results of MOPSO and NSGA-II are compared with the second version of Augmented Epsilon Constraint Method (AUGMECON 2) in small size problems and with together in large size problems (projects with more than 8 activities) for which the ability to accurately solve in a reasonable time does not exist. The results show that in most of the criteria and for all sizes of the problem, NSGA-II has better performance than MOPSO. Also, to ensure the applicability of the proposed model and how to implement it in real-world conditions, the fifth section of the Mianeh-Bostanabad-Tabriz railway infrastructure project has been investigated.
