Industrial Engineering, University of Kurdistan
Project success is assessed based on various criteria, every one of which enjoys a different level of importance for the beneficiaries and decision makers. Time and cost are the most important objectives and criteria for the project success. On the other hand, reducing the risk of finishing activities until the predetermined deadlines should be taken into account. Having formulated the problem as a multi-objective planning problem, the present study aims at minimizing the project completion time as well as maximizing the net present value and project flexibility by taking into account the resource constraints and precedence relations. Here the flexibility of project is calculated by considering a free float for each activity and maximizing the sum of these flotation times. Although most of the researches considered the resources as non-renewable resources, here the resources are considered as renewable ones. Moreover, performing each activity may be possible in various states of using resources (mode) which can change the project completion time and cost. Owing to the complexity of the problem, the Multi Objective Simulated Annealing Meta-heuristic Algorithm is used to solve the proposed model. In doing so, first a feasible answers is proposed and then, using the aforementioned algorithm, it was attempted to find Pareto answers. For accrediting the algorithm, four benchmark problems have been considered. Since the algorithm performed well in finding the optimal answers to the benchmark problems, it was used to find the optimal answer of large scale problems.