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RESEARCH ARTICLE

Structural feasibility handling in non-convex economic dispatch: Integrating fuzzy C-means clustering with a diagnostically-redesigned genetic algorithm

Rifki Rahman Nur Ikhsan1,2 ,  Efri Suhartono1,2 ,  Jangkung Raharjo1,2* ,  Lindiasari Martha Yustika1,2 ,  I Gede Putu Oka Indra Wijaya1,2
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1 School of Electrical Engineering, Telkom University, Jl. Telekomunikasi No. 1, Terusan Buah Batu, Bandung, West Java , Indonesia
2 Center of Excellence of Sustainable Energy and Climate Change, Telkom University, Jl. Telekomunikasi No. 1, Terusan Buah Batu, Bandung, West Java , Indonesia
IJOCTA, 026400306 https://doi.org/10.36922/IJOCTA026400306
Received: 29 September 2026 | Revised: 20 October 2026 | Accepted: 21 October 2026 | Published online: 10 November 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Practical thermal economic dispatch (ED) problems with valve-point effects (VPE), prohibited operating zones (POZ), ramp-rate limits, and unit commitment (UC) decisions are non-smooth, non-convex, and fragmented, which defeats gradient-based solvers. This paper presents a feasibility-aware computational intelligence framework—the Fuzzy C-Means Population-Based Genetic Algorithm (FCM-PbGA)—that embeds commitment-consistent encoding, FCM-guided initialisation, ramp-feasible bounds, POZ-aware projection, and Lamarckian refinement in a single-population evolutionary architecture. The framework is evaluated on the IEEE 15-unit, 24-hour benchmark (30 trials). The initial island-based architecture (Stage 1) achieves $662,173 ± $2,151. Budget-matched re-runs and ablation isolate architecture from budget: fixed six-island partitioning proves counterproductive, and the matched GA outperforms Stage 1. Three redesigns follow: adaptive merging, reheating, POZaware crossover and fractional seeding close 49% of the gap; corrected operators close an additional 36%; and removing islands entirely (v4) reaches $655,073.62 ± $1,469—a statistical tie with the matched GA (p = 0.199, d = −0.34) under published conditions, and a significant lead (p = 5.2 × 10−6, d = −1.34) with correctly loaded POZ sets and strict repair. Zero power-balance, ramp-rate, POZ, and generation-limit violations are verified over 10,800 unit-hours. The study demonstrates a diagnose-then-redesign methodology for constrained engineering scheduling.

Keywords
Computational intelligence
Hybrid evolutionary algorithm
Fuzzy C-means clustering
Non-convex economic dispatch
Valve-point loading effect
Prohibited operating zones
Unit commitment
Funding
This research was funded by the Directorate of Research and Community Service at Telkom University under Agreement/Contract Letter No. 009/LIT06/PPM-LIT/2025.
Conflict of interest
The authors declare that they have no competing interests.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing
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