In 1983, J.E. Spingarn introduced what he called the Partial Inverse Method in the framework of Mathematical Programming. Since his initial articles, numerous applications have been given in various fields including Lagrangian multipliers methods, location theory, convex feasibility problems, analysis of data, economic equilibrium problems. In a first part of this paper we give a survey of these applications. Then by means of optimization problems relevant to location theory such as single and multifacility minimisum or minimax location problems, we examine the main advantages of the algorithm and we point out its drawbacks mainly concerning the rate of convergence. We study how different parameters can be introduced to get a significant reduction in the number of iterations and we give numerical results.