<p>Floorplanning is a critical step in the design of integrated circuits, directly influencing performance metrics such as functionality, yield, and stability. This work addresses the complexities of floor planning by proposing a novel multi-objective hybrid optimization model, the Dingo Modified Arithmetic Optimization Model (DM-AOM), which utilizes the Sequence Pair technique for non-slicing floorplans. The research problem focuses on optimizing key factors such as wire length and layout area while minimizing delays in circuit operation. Our contributions include the development of the DM-AOM, which effectively combines the strengths of the Dingo Optimizer and Arithmetic Optimization Algorithm to achieve enhanced optimization outcomes. The proposed DM-AOM significantly reduces wire length and layout area, achieving a best-case fitness value of 9268.3 on the ami33.yal benchmark, outperforming traditional optimization methods. The importance of this research resides in its capacity to enhance circuit design efficiency, resulting in smaller layouts and superior performance in real-world applications. Moreover, the adaptability of DM-AOM makes it suitable for complex optimization tasks in Wireless Sensor Networks (WSNs), where efficient resource allocation, communication path selection, and node-level energy optimization are essential. The algorithm’s capacity to minimize communication overhead and delay can be extended to routing decisions in wireless topologies. Future investigations could explore the scalability of the DM-AOM and its adaptability to dynamic design environments, further enhancing the relevance of this approach in the evolving landscape of wireless and embedded systems.</p>