A Projection-Based Evolutionary Algorithm for Multi-Objective and Many-Objective Optimization

Many-objective optimization problems (MaOPs) are challenging in scientific research. Research has tended to focus on algorithms rather than algorithm frameworks. In this paper, we introduce a projection-based evolutionary algorithm, MOEA/PII. Applying the idea of dimension reduction and decomposition, it divides objective space into projection plane free dimension(s). The balance between convergence diversity is maintained using Bi-Elite queue. MOEA/PII not only an but also framework. We can choose decomposition-based or dominance-based be algorithm. When framework, exhibits better performance. compare performance with evaluated by benchmark test instances DTLZ1-7 WFG1-9 3, 5, 8, 10, 15 objectives IGD-metric HV-metric. addition, investigated its superior wireless sensor networks deployment problem C-metric. Moreover, determining domain for objects reduces time makes solution set more responsive user needs.