Optiflow-DNA: A DNA Computing-Based Optimization Algorithm for Real-Time Workflow Scheduling In Smart Factories

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.