چكيده به لاتين
In decentralized projects, most of the costs are related to investment costs, material purchase costs, holding costs, logistics costs, and other peripheral costs of project implementation. For this reason, the simultaneous planning of these items and the scheduling of activities can reduce total costs. This research investigates the decentralized multi-projects scheduling problem with the aim of minimizing completion time of projects and the costs of project implementation. Project implementation costs include the cost of resource pool construction, resource transferring costs, material purchase costs, holding costs, and resource deterioration costs. To further explore this issue, three different problems are presented with different assumptions. In order to solve these problems, the mathematical programming models, heuristic methods, and meta-heuristic algorithms are developed. Computational results show the efficiency of heuristic and meta-heuristic algorithms. At the end, a case study of decentralized multi-projects scheduling problem in Iran is examined with the assumptions discussed in this thesis. The results of this case study show that the integrated model can reduce the total project execution costs up to 9.9%.
