Abstract: In this study, a binary version of the Ivy-inspired algorithm (IVY) was designed and evaluated to solve the 0–1 Knapsack Problem. The Knapsack Problem is a classical combinatorial optimization problem with applications in resource allocation, scheduling, and project planning. Due to the exponential complexity of its search space, efficient and effective algorithms are required to solve it. The BiIVY version combines a directed growth mechanism, a penalty function, and a specialized repair algorithm, enabling it to find higher-quality solutions with fewer iterations compared to conventional algorithms. Algorithm parameters were determined based on previous studies and experimental trials. The performance of BiIVY was evaluated on 25 standard datasets (L1–L25) and compared with Binary Flower Pollination Algorithm (BFPA) and Binary Sine-Cosine Algorithm (BSCA). Friedman mean-rank test results indicate that BiIVY generally outperforms the other algorithms in terms of total profit and iteration count, providing optimal or near-optimal solutions with fewer iterations, which demonstrates the effectiveness and capability of the proposed algorithm in solving complex combinatorial problems.