Quantum Computing for Optimization Problems: A Comparative Analysis with Classical Approaches
Main Article Content
Abstract
Quantum computing has emerged as a powerful tool for solving complex optimization problems across various domains. This paper provides a comparative analysis of quantum and classical approaches to optimization, focusing on applications in logistics, finance, and machine learning. Using quantum algorithms such as QAOA and Grover's search, we benchmark performance against traditional methods like linear programming and metaheuristics. Results indicate significant speedups for specific problem classes, while challenges in scalability and error correction are identified. Future directions for hybrid quantum-classical systems are proposed.
Downloads
Article Details
How to Cite
References
Pillai, S. E. V. S., & Polimetla, K. (2024, February). Analyzing the Impact of Quantum Cryptography on Network Security. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE.
Pillai, S. E. V. S., & Polimetla, K. (2024, February). Mitigating DDoS Attacks using SDN-based Network Security Measures. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-7). IEEE.
Whig, P., & krishna Adusumilli, S. B. (2024). Leveraging AI and Machine Learning for Optimizing Supply Chain Management in Healthcare: A Predictive and Prescriptive Approach. International Scientific Journal for Research, 6(6).
Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.
Chintala, S. (2024). Strategies for Enhancing Data Engineering for High Frequency Trading Systems. International IT Journal of Research, ISSN: 3007-6706, 2(3), 1-10.
Dodda, S., Chintala, S., Kanungo, S., Adedoja, T., & Sharma, S. (2024). Exploring AI-driven Innovations in Image Communication Systems for Enhanced Medical Imaging Applications. Journal of Electrical Systems, 20(3s), 949-959.
Adusumilli, S. B. K. (2023). TOWARDS ENERGY-EFFICIENT AIML INFERENCE ON EDGE DEVICES SOFTWARE SOLUTIONS AND CHALLENGES. Journal of Engineering Sciences, 14(11).
Whig, P., & Adusumilli, S. B. K. (2023). Enhancing Healthcare Delivery Through AI-Driven Supply Chain Innovations: A Case Study Perspective. International Transactions in Artificial Intelligence, 7(7).
Chintala, S. Analytical Exploration of Transforming Data Engineering through Generative AI‖. International Journal of Engineering Fields, ISSN, 3078-4425.
Narani, S. R., Ayyalasomayajula, M. M. T., & Chintala, S. (2018). Strategies For Migrating Large, Mission-Critical Database Workloads To The Cloud. Webology (ISSN: 1735-188X), 15(1).
Chintala, S., Jindal, M., Mallreddy, S. R., & Soni, A. (2024). Enhancing Study Space Utilization at UCL: Leveraging IoT Data and Machine Learning. Journal of Electrical Systems, 20(6s), 2282-2291.
Ayyalasomayajula, M. M. T., Chintala, S., & Narani, S. R. INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING.
Chintala, S., Kunchakuri, N., Kamuni, N., & Dodda, S. (2024, October). Developing an Adaptive Educational Chatbot for Personalized SQL Tutoring. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-5). IEEE.
Dodda, S., Chintala, S., Kunchakuri, N., & Kamuni, N. (2024, October). Enhancing Microservice Reliability in Cloud Environments Using Machine Learning for Anomaly Detection. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-5). IEEE.
Chintala, S. (2023). Improving Healthcare Accessibility with AI-Enabled Telemedicine Solutions. International Journal of Research and Review Techniques, 2(1), 75-81.
Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2021). AI-Powered Cybersecurity Solutions for Threat Detection and Prevention. International Journal of Creative Research In Computer Technology and Design, 3(3).
Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2020). Leveraging AI for Real-Time Sentiment Analysis in Social Media Networks. International Numeric Journal of Machine Learning and Robots, 4(4).
Kamuni, N., Dodda, S., Chintala, S., & Kunchakuri, N. (2024, October). Optimizing Machine Translation: A Benchmarking Suite for Efficiency and Quality Enhancement. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-7). IEEE.
Adusumilli, S., Damancharla, H., & Metta, A. (2020). Machine Learning Algorithms for Fraud Detection in Financial Transactions. International Journal of Sustainable Development in Computing Science, 2(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/639
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94