<![CDATA[Rapid technological development requires systems to solve decision-making and optimization problems efficiently, including shortest-path search, scheduling, data archiving, and resource allocation. This study aims to analyze the performance and effectiveness of a greedy algorithm-based system and evaluate its functionality using the black-box testing method. In addition to measuring the system's success rate in processing test data, this study also examines the limitations of the greedy algorithm, particularly its tendency to become trapped in local optima, while improving the efficiency of employee skill input and generating conflict-free scheduling. The research applies the greedy algorithm as the primary optimization approach, while system validation is conducted through black-box testing by examining the consistency between system inputs and outputs without evaluating the internal source code. The testing results on 24 test cases demonstrate a success rate of 91.6%, with 22 valid cases and 2 invalid cases (8.3%). The invalid cases confirm the inherent limitation of the greedy algorithm in achieving the global optimum under certain conditions. Therefore, it can be concluded that the proposed greedy algorithm-based system performs well, is reliable, and is suitable for practical implementation due to its high level of functional success.]]>
Copyrights © 2026
