Akran denetiminde hakem atamaları için alternatif eniyileme modelleri

Today, most of the clinical and academic research are financed by the funding organizations. These organizations employ a selection process to select the proposals that are likely to have the highest return for the society. At this point, the selection of the proposals to be funded becomes crucial. The main objective of this thesis is to propose exact and heuristic approaches to increase the success rate of the selection of better proposals for funding. We focus on the process of proposal evaluation by referees and the scope of this thesis is to develop solution methodologies to assign proposals to referees so as to maximize a certain set of criteria subject to a set of restrictions. We develop two integer linear programming models. For larger instances, we propose heuristic methods. We conduct computational experiments on randomly generated instances in an attempt to assess the performances of our mathematical models and heuristic approaches. In comparison with previously proposed optimization models and heuristic approaches, our computational experiments reveal the promising performance of our solution approaches.