A Co-joint Deterministic Search Direction Sampling Procedure with Probabilistic Soft Approach

Abstract

Since hard continuous optimization models contain more than one solution and even continuum
solution, it is impossible to seek all the solution by using the existent optimization methods.
Therefore, in this paper we introduce a co-joint deterministic and probabilistic approach which
modifies a soft approach for solving hard continuous optimization models. An algorithm of co-joint
approach and several numerical experiments have been presented in this paper. The special
numerical test results have shown that the co-joint approach is more effective than soft approach
algorithm. Fortunately, we have found that the co-joint algorithm can be used to determine whether
the optimization model is hard continuous optimization models or not.