Optiflow-DNA: A DNA Computing-Based Optimization Algorithm for Real-Time Workflow Scheduling In Smart Factories
DOI:
https://doi.org/10.71086/IAJSE/V12I2/IAJSE1225Keywords:
DNA Computing, Smart Factories, Workflow Scheduling, Real-Time Optimization, Bio-Inspired Algorithms, Industry 4.0, Cyber-Physical Systems.Abstract
In the context of Industry 4.0, adaptive manufacturing systems, cost efficiency, and productivity focus on smart
factories around the world. In this regard, controlling workflow scheduling for maximum productivity remains a
challenge. This is why this paper presents OptiFlow-DNA: a real-time workflow scheduling algorithm inspired by
DNA computing principles. Through the parallelism, data storage, and energy efficiency of DNA, OptiFlow-DNA
executes complex dynamic scheduling problems in a manufacturing environment. The algorithm's biochemical
techniques allow for rapid task sequence encoding while exploring solution spaces. Simulated tests conducted within
scenario based smart factory environments show OptiFlow-DNA outperforms previous metaheuristics based
approaches with less execution time and better scalability, adaptability to changes, and retention of real-time
constraints. Results demonstrate OptiFlow-DNA’s benefits for cyber-physical production systems. Besides boasting
operational advancements alongside bio-inspired optimization in industrial settings, the proposed method opens up
possibilities for integrating molecular computing into real-time decision-making systems.
