Immune Algorithms (IAs) are categorized into three classes. Although the major type of IAs using clonal selection have been widely investigated and applied to Multi-objective Optimization Problems (MOPs), IAs based on self-regulation by suppressor T-cells have not. This paper focuses on the latter IAs and proposes Non-dominated Prioritized IA (NPIA) which is designed to solve MOPs with keeping the characteristics of IAs without clonal selection. Experimental results have shown NPIA's search performance competitive with MOGAs and possibility of IA-based multi-objective optimization.