Multi-objective resistance-capacitance optimization algorithm: An effective multi-objective algorithm for engineering design problems
Sowmya Ravichandran,
Premkumar Manoharan,
Deepak Kumar Sinha,
Pradeep Jangir,
Laith Abualigah,
Thamer A.H. Alghamdi
Affiliations
Sowmya Ravichandran
Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India
Premkumar Manoharan
Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, Karnataka, India; Corresponding author. Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, Karnataka, India.
Deepak Kumar Sinha
Department of Computer Science and Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bangalore, 562112, India
Pradeep Jangir
Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India; Jadara University Research Center, Jadara University, Irbid 21110, Jordan
Laith Abualigah
Computer Science Department, Al al-Bayt University, Mafraq 25113, Jordan; Artificial Intelligence and Sensing Technologies (AIST) Research Center, University of Tabuk, Tabuk, 71491, Saudi Arabia; MEU Research Unit, Middle East University, Amman, 11831, Jordan; Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan; Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India
Thamer A.H. Alghamdi
Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff, CF24 3AA, UK; Electrical Engineering Department, Faculty of Engineering, Al-Baha University, Al-Baha, 65779, Saudi Arabia; Corresponding author. Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff, CF24 3AA, UK
Focusing on practical engineering applications, this study introduces the Multi-Objective Resistance-Capacitance Optimization Algorithm (MORCOA), a new approach for multi-objective optimization problems. MORCOA uses the transient response behaviour of resistance-capacitance circuits to navigate complex optimization landscapes and identify global optima when faced with many competing objectives. The core approach of MORCOA combines a dynamic elimination-based crowding distance mechanism with non-dominated sorting to generate an ideal and evenly distributed Pareto front. The algorithm's effectiveness is evaluated through a structured, three-phase analysis. Initially, MORCOA is applied to five benchmark problems from the ZDT test suite, with performance assessed using various metrics and compared against state-of-the-art multi-objective optimization techniques. The study then expands to include seven problems from the DTLZ benchmark collection, further validating MORCOA's effectiveness. The final phase involves applying MORCOA to six real-world constrained engineering design problems. Notably, the optimization of a honeycomb heat sink, which is crucial in thermal management systems, is a significant part of this study. This phase uses a range of performance measures to assess MORCOA's practical application and efficiency in engineering design. The results highlight MORCOA's robustness and efficiency in both real-world engineering applications and benchmark problems, demonstrating its superior capabilities compared to existing algorithms. The effective use of MORCOA in real-world engineering design problems indicates its potential as an adaptable and powerful tool for complex multi-objective optimization tasks.
