A Comparative Study of Optimization Methods for a Resource Allocation in Mobile Communications

This thesis addresses a resource allocation problem in mobilecommunications. The objective is to allocate a set of resource blocks to a set of users in a way that the total transmission rate between them is maximized. To make the model applicable for real use, it is assumed that each user receives a common data rate from all resource blocks allocated to the corresponding user. Three different optimization methods, Mixed Integer Programming (MIP), Tabu Search (TS) meta-heuristic, and Constraint Programming (CP), were applied to solve the problem. The methods were then compared against each other to examine which method is the most promising for the time scale needed for real use. To simulate real-world scenarios, three sets of instances were used to compare the performance of the proposed methods. The results demonstrated the efficiency of the MIP model and TS algorithm in terms of solution quality and computation time. The MIP model could optimally solve the instances in 2.5 to 5 seconds, while the TS algorithm could obtain near optimalsolutions on the majority of instances in 0.5 to 0.8 seconds