This paper presents a new algorithm for solution of the nonlinear optimal scheduling problem. This algorithm is named the iteration particle swarm optimization (IPSO). A new index, called iteration best, is incorporated into particle swarm optimization (PSO) to improve the solution quality and computation efficiency. IPSO is applied to solve the unit commitment with probabilistic reserve problem of a power system. The outage cost as well as fuel cost of thermal units was considered in the unit commitment program to evaluate the level of spinning reserve. The optimal scheduling of on line generation units was reached while minimizing the sum of fuel cost and outage cost. A 48 unit power system was used as a numerical example to test the new algorithm. The optimal scheduling of on line generation units could be reached in the testing results while satisfying the requirement of the objective function. (c) 2006 Elsevier Ltd. All rights reserved.