Drawing on the benchmarking theory in the business management, a new search method, benchmarking-based optimization algorithm (BOA), is proposed in this paper. BOA provides a competitive learning mechanism based on dynamic niche according to the core values of benchmarking. Through imitation and learning, all the individuals within a population are able to approach to the high yielding regions in the solution space and seek out the optimal solutions quickly. Further, the formidable problem of maintaining the diversity of population is effectively resolved through the self-organizing learning process of the niche system and its friendly interaction with the environment. In this paper, the main differences between BLA and the existing intelligent optimization methods, sush as genetic algorithm (GA), are analyzed. The comparative experiments show that BLA is robust and able to perform friendly interactive learning with the environment, and its search speed and optimization ability is far superior to the existing intelligent optimization methods.