This study proposes a new and improved Lipschitz optimization algorithm to obtain an ε-optimal solution for solving the transportation fleet maintenance-scheduling problem. It employs a procedure based on slope-checking and step-size comparison mechanisms to improve the computational efficiency of the Evtushenko algorithm. Our numerical experiments used 36,000 randomly generated instances to compare the run time and solution quality of our proposed algorithm with the alternative approach in the literature. Our results indicate that the run time of the proposed algorithm could be significantly improved by more than 80% in over 50% of instances in our numerical experiments. We conclude that our proposed algorithm significantly improves the computational efficiency of the conventional Evtushenko algorithm.
- Lipschitz programming