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NSGA-III-based multi-objective optimization of a diesel–biodiesel engine with isobutanol and ZnO nanoparticles: A comparative evaluation using VIKOR and TOPSIS

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  • Ai, Wenbo
  • Cho, Haeng Muk

Abstract

This study systematically investigates the effects of isobutanol and ZnO nanoparticles on the performance and emission characteristics of a diesel-biodiesel blend. Fuel samples with varying proportions of isobutanol and concentrations of ZnO nanoparticles were prepared and tested at 1400 rpm under three engine load conditions. RSM coupled with a Box-Behnken Design was employed to establish predictive models. The results revealed that isobutanol effectively suppressed NOx formation by lowering in-cylinder combustion temperatures, whereas ZnO nanoparticles, acting as a combustion catalyst, significantly enhanced BTE while reducing BSFC, CO, and HC emissions. Subsequently, multi-objective optimization was performed using NSGA-III, with comprehensive weights derived from integrated EWM and FAHP. Fuzzy VIKOR and Fuzzy TOPSIS were then applied for robust ranking under uncertainty. The Fuzzy VIKOR solution excelled in NOx reduction, while the Fuzzy TOPSIS solution prioritized higher BTE and lower BSFC.

Suggested Citation

  • Ai, Wenbo & Cho, Haeng Muk, 2026. "NSGA-III-based multi-objective optimization of a diesel–biodiesel engine with isobutanol and ZnO nanoparticles: A comparative evaluation using VIKOR and TOPSIS," Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:energy:v:350:y:2026:i:c:s0360544226003750
    DOI: 10.1016/j.energy.2026.140273
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