Nowadays, a project-winning environment is very competitive. In order to be successful and make profit, a contractor should start planning in advance and decide about what projects to bid. A prominent contractor should bid on projects for which his chances of winning are good enough or on projects for which the profit is high enough such that bidding would be worth consuming the resources needed for preparing the bid. The chances of winning bids are related to many factors but among all, degree of eminence (previous works) and price are the most important. In this thesis we have developed an optimization model that maximizes an index that takes both of these factors into consideration. Genetic Algorithm is used to solve this optimization model.The output of this model is the most beneficial set of projects and their respected optimal bid markups that will help the contractor make the most intuitive selection which, in return, benefits him/her the most at present and in the future.