The utilization of parallel search techniques is increasingly recognized for its efficacy in modeling, simulating, and comprehending intricate real-world phenomena. This paper explores the application of parallel search techniques to address Prostate Cancer classification. Emphasis is placed on ensuring that each point within the search space is traversed only once, leading to the acquisition of optimized values. The methodology entails employing a straightforward operation to explore points within a search space of 10n dimensions. The proposed technique efficiently navigates through every search point precisely once, ensuring comprehensive coverage of the search space. The selection of search points throughout the entirety of the search space is facilitated by a method termed RLC.