Focus and Scope

The International Journal of Industrial Optimization (IJIO) publishes original research articles, reviews, and case studies that explore the development and application of optimization techniques to solve complex industrial problems. The journal focuses on the integration of computational methods, especially Artificial Intelligence (AI)-based approaches, to improve decision-making, efficiency, and sustainability in industrial systems.

IJIO encourages contributions in, but not limited to, the following areas:

  • Mathematical modeling and optimization for production, logistics, and supply chain systems

  • AI-driven optimization techniques, including machine learning, deep learning, and reinforcement learning applied to industrial challenges

  • Heuristic and metaheuristic methods (e.g., Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization) for large-scale, nonlinear, and multi-objective problems

  • Smart manufacturing and intelligent process optimization using AI technologies

  • Hybrid models combining simulation, optimization, and AI for adaptive and real-time decision-making

  • Sustainable optimization approaches that reduce environmental impact and promote responsible production

  • Human-in-the-loop optimization and robust decision-making under uncertainty and dynamic conditions

The journal seeks interdisciplinary research that contributes to both theoretical advancements and practical solutions across various industrial sectors.

IJIO also supports research that aligns with the United Nations Sustainable Development Goals (SDGs), particularly:

  • SDG 9 – Industry, Innovation, and Infrastructure

  • SDG 12 – Responsible Consumption and Production

  • SDG 8 – Decent Work and Economic Growth

  • SDG 13 – Climate Action

Through this scope, IJIO aims to promote innovation, sustainability, and resilience in the optimization of industrial systems powered by Artificial Intelligence.