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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Helmy Widyantara
Telkom University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Double direction optimization: a new metaheuristic that performs exploitation and exploration simultaneously Purba Daru Kusuma; Helmy Widyantara
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2874-2884

Abstract

This research constructs a novel method called double direction optimization (DDO). DDO is constructed based on swarm intelligence (SI) approach and it does not use any metaphor. As its name suggests, it employs a novel algorithm by performing exploitation and exploration simultaneously which is transformed into two sequential searches. In the 1st search, the motion toward the highest quality agent is combined with the motion toward a randomly taken higher quality agent. In the 2nd search, the motion toward the finest entity is combined with the motion relative to a randomly taken agent. In this work, the efficacy of the DDO is assessed using three use cases: 23 functions, four engineering problems, and an economic emission dispatch (EED) problem. In this assessment, there are five metaheuristics that become the benchmark: crayfish optimization algorithm (COA), hiking optimization (HO), osprey optimization algorithm (OOA), carpet weaver optimization (CWO), and dollmaker optimization algorithm (DOA). The result indicates the supremacy of DDO in high dimension functions and competitiveness of DDO in fixed dimension multimodal functions, four engineering problems, and the EED problem.
Conditional toggle algorithm: an adaptive metaheuristic and its implementation on handling engineering problems Purba Daru Kusuma; Helmy Widyantara
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10048

Abstract

There have been numerous new metaheuristic algorithms in this decade. Unfortunately, the attention on taking stagnation is still less considered so that it is difficult to find new metaheuristic algorithms that are enriched with stagnation taking mechanism. This work introduces a new method called conditional toggle algorithm (CTA). CTA is designed to be adaptive on facing enhancement and stagnation during iteration as its novelty. When enhancement occurs, the exploitation-focused look is applied. Meanwhile, the exploration-focused look is applied when stagnation occurs. The efficacy of CTA is then measured by implementing to solve three cases: 23 functions, 4 engineering design problems, and economic emission dispatch (EED) problem in Java-Bali power system in Indonesia. CTA is compared with five new metaheuristic algorithms. The evidence provides that CTA is supreme in taking high dimension functions and competing in taking fixed dimension functions. CTA is also supreme in taking pressure vessel and speed reducer design problems and the EED problem. But its performance is average in taking welded beam and spring design problems. In the future, CTA can be modified with other metaheuristic algorithms to enhance its performance and challenged to take broader problems, especially in electrical engineering fields.
Co-Authors Purba Daru Kusuma