MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving Engineering Design Problems  

作　　者：Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar 

机构地区：[1]Computer Science Department,University of M’sila,Ichebilia,M’sila,28000,Algeria [2]Computer ScienceDepartment,Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridj,Bordj BouArreridj,34000,Algeria [3]Department of Computer Engineering,College of Computer and Information Sciences,King Saud University,Riyadh,11543,Saudi Arabia [4]Operations Research Department,Faculty of Graduate Studies for Statistical Research,Cairo University,Giza,12613,Egypt [5]Applied Science Research Center,Applied Science Private University,Amman,11931,Jordan [6]Faculty of Mathematics,Otto-von-Guericke University,Magdeburg,39016,Germany [7]University Centre for Research and Development,Chandigarh University,Mohali,140413,India [8]Department of Electrical and Computer Engineering,Shahid Beheshti University,Tehran,14399,Iran [9]DTU AI and Data Science Hub(DAIDASH),Duy Tan University,Da Nang,550000,Vietnam

出　　处：《Computer Modeling in Engineering & Sciences》2025年第4期967-1008,共42页工程与科学中的计算机建模(英文)

基　　金：funded by Researchers Supporting Programnumber(RSPD2024R809),King Saud University,Riyadh,Saudi Arabia.

摘　　要：Multi-objective optimization is critical for problem-solving in engineering,economics,and AI.This study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct objectives.Our approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto front.Our comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume metric.This paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关 键 词：Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]