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Journal of Fuzzy Systems and Control (JFSC)
Published by Peneliti Teknologi Teknik Indonesia
ISSN : -     EISSN : 29866537     DOI : https://doi.org/10.59247/jfsc.v1i1.24
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Journal of Fuzzy Systems and Control is an international peer review journal that published papers about Fuzzy Logic and Control Systems. The Journal of Fuzzy Systems and Control should encompass original research articles, review articles, and case studies that contribute to the advancement of the theory and application of fuzzy systems and control, and their integration with other technologies, such as artificial intelligence, machine learning, and optimization.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 111 Documents
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A Heuristic Evolutionary Multi-Objective Method for Indoor LED Lighting Optimization with DIALux and Experimental Validation Faizal Abdul Rouf Asyahari; W Warindi; I Inayati
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.425

Abstract

Indoor lighting optimization is commonly addressed using population-based metaheuristic algorithms such as the genetic algorithm and multi-objective particle swarm optimization. However, these methods generally rely on crossover, mutation, or swarm-update operators, resulting in relatively high computational complexity while placing greater emphasis on algorithmic optimization than on practical implementation and experimental validation. This study proposes a heuristic evolutionary multi-objective method for indoor LED lighting optimization that integrates constraint-aware candidate generation, lexicographical multi-objective ranking, and photometric evaluation to determine energy-efficient lighting layouts. Unlike conventional evolutionary algorithms, the proposed method directly generates feasible candidate solutions without employing crossover or mutation operators, thereby reducing computational complexity while maintaining solution quality for structured indoor lighting layouts. The optimized lighting configurations were validated through numerical photometric calculations based on SNI 6197:2020, DIALux simulations using a Lambertian photometric model, and direct luxmeter measurements. Experimental validation confirmed that the optimized lighting layouts satisfied the required illuminance and uniformity criteria, with average illuminance deviations ranging from 6% to 17% between computational predictions and practical measurements. The optimized lighting layouts also achieved Lighting Power Density (LPD) values ranging from 4.89 to 5.50 W/m², which are below the maximum allowable limit specified by SNI 6197:2020, demonstrating that the proposed optimization framework effectively reduces energy consumption while maintaining the required lighting performance. The proposed method provides a practical alternative to conventional evolutionary optimization methods by integrating efficient multi-objective optimization with comprehensive simulation and experimental validation, enabling reliable, energy-efficient, and standards-compliant indoor LED lighting design.

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