A Master of Science thesis in Engineering Systems Management by Nour Ahmed Kashwani entitled, “Multi- Mode Resource Constrained Project Scheduling Problem with Material Ordering to Maximize NPV”, submitted in April 2018. Thesis advisor is Dr. Abdulrahim Shamayleh. Soft and hard copy available.
Project management is critical for companies to stay competitive; nowadays it is regarded as a very high priority. The project management scheduling process of deciding when an activity starts and how resources will be used will highly impact the project duration and cost. A realistic schedule will minimize the chances of failure. Traditionally, the objective of makespan minimization to plan the overall project has been the concept; however, it is critical to incorporate the financial aspect of the project and schedule the activities in such a way that will maximize the net present value (NPV). In this thesis, a mathematical model for the multi-mode resource-constrained project scheduling problem with material ordering to maximize the net present value (MMRCPSPMO) is developed. The model is subjected to precedence, deadline, renewable and non-renewable resources and capital availability constraints. In addition, penalties are imposed in case of any delays. Project scheduling and material ordering decisions are emphasized to determine the time and quantity of an order because setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. A sensitivity analysis has been performed on the model to see the effect of varying the ordering costs, holding costs and network sizes and complexities. In addition, the variation of both holding and ordering costs at the same time has been performed. The analysis results showed that once the ordering cost is increased, the objective function is affected and hence, the model tends to minimize the overall material orders placed in order to obtain the maximum desired NPV. On the other hand, when the holding cost increases, the model tends to reduce the inventory stored and order the desired materials when needed to avoid storing inventory with high holding costs and longer durations. Furthermore, sensitivity analysis has been performed on 86 different networks with varied sizes of 7, 10, 12, 14, 16, 18, 20, 22 and 25 with a network complexity of 0.2, 0.4, 0.6 and 0.8. The results generated have shown that once the project’s network reaches 20 activities with a network complexity of 0.8, the model tends to take a long computational time; therefore, a heuristic approach is developed in order to minimize the computational time for large size projects