In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS) In competitive power markets, electricity prices are determined by balance between demand and supply in electric power exchanges or bilateral contracts. Therefore it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling method, firstly, electricity prices are forecasted for the targeted period using proposed aggregated bidding model. Secondly, the optimal combinatorial maintenance-scheduling problem is solved by using Reactive Tabu Search in the light of the electricity prices forecasted. This method proposes a new objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss of Maintenance (OLM) is adopted to maximize the profit of Generation Companies (GENCOS). Finally, the proposed maintenance scheduling is applied to a practical power system test model to verify the advantages and effectiveness of the method.