Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

Abstract: This paper presents a new phase 1 simplex algorithm for solving linear programming problems. In the algorithm, first, the equation with the auxiliary objective function at the optimality as ...

We consider discounted Markov decision processes (MDPs) with countably-infinite state spaces, finite action spaces, and unbounded rewards. Typical examples of such MDPs are inventory management and ...

SoPlex is an optimization package for solving linear programming problems (LPs) based on an advanced implementation of the primal and dual revised simplex algorithm. It provides special support for ...

Abstract: A new heuristic optimization algorithm is presented to solve the nonlinear optimization problems. The proposed algorithm utilizes a stochastic method to achieve the optimal point based on ...