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This study proposes a novel approach for optimal coordination of Directional Overcurrent Relays (DOCRs) in power distribution networks by employing the Differential Search Algorithm (DSA), complemented by a graph-theoretic network topology processor. The primary objective is to minimize relay operation time while maintaining the Coordination Time Interval (CTI) within an ideal range (0.3–0.8 seconds), thus ensuring selective and reliable protection under various fault scenarios, including those influenced by Distributed Energy Resources (DERs). The research adopts a non-linear optimization framework where the decision variables—Time Multiplier Settings (TMS), Plug Settings (PS), and time-inverse relay characteristics—are optimized. The study formulates the coordination problem under relay setting constraints, operational time limits, and CTI constraints. A detailed methodology involving fault analysis, load flow studies, selectivity constraint refinement, and relay setting computation ensures accurate coordination. DSA's performance is benchmarked against MATLAB-based Sequential Quadratic Programming (SQP) and the Seeker Algorithm across IEEE 3-bus and 8-bus test systems. The proposed method consistently achieves lower total operating times and better CTI compliance, eliminating miscoordination observed in other methods. Teaching Learning-Based Optimization (TLBO), a parameter-independent algorithm, is also integrated to improve robustness and reduce dependency on algorithm-specific tuning. Results confirm the superiority of the DSA approach in optimizing DOCR settings, ensuring protection integrity even in dynamic, DER-penetrated environments. The proposed hybrid coordination strategy, with adaptive relay characteristics, is scalable, efficient, and applicable to real-time distribution systems, demonstrating significant advancements over traditional optimization techniques.