Journal of Intelligent Operations and Decision Sciences (JIODS) is an international, peer-reviewed scholarly journal dedicated to intelligent decision-making, operations research, decision analytics, and optimization, with a particular focus on the development and application of analytical, computational, and data-driven approaches for understanding, evaluating, predicting, planning, and optimizing complex systems.
JIODS is positioned at the intersection of operations research, decision sciences, artificial intelligence, data analytics, mathematical modelling, and computational optimization. The journal focuses on advancing analytical methodologies and intelligent computational approaches that transform complex information, data, and knowledge into meaningful insights, effective decisions, and improved operational performance.
The journal promotes intelligent operations and decision sciences as an integrated multidisciplinary perspective combining mathematical modelling, computational intelligence, data-driven analytics, optimization, and decision-support technologies. Contributions should demonstrate how proposed methodologies and analytical frameworks advance decision-making capabilities, generate new analytical insights, improve operational efficiency, or support more effective planning and resource allocation.
JIODS particularly welcomes research integrating operations research and decision sciences with artificial intelligence, machine learning, mathematical programming, multi-criteria and multi-objective decision analysis, optimization algorithms, simulation, forecasting, predictive and prescriptive analytics, and intelligent decision-support systems. Relevant topics also include stochastic and robust optimization, fuzzy and uncertainty-aware decision models, evolutionary and metaheuristic algorithms, network optimization, scheduling, resource allocation, risk and resilience analysis, explainable artificial intelligence, and hybrid analytical and computational frameworks.
The journal encourages methodological, mathematical, and computational innovation when it addresses clearly defined decision-making or operational problems. Studies introducing new optimization algorithms, decision models, aggregation procedures, weighting techniques, ranking methods, computational frameworks, or related methodologies should clearly explain the research problem they address and demonstrate their theoretical, methodological, computational, or practical contributions. The journal particularly values methodological rigor, analytical relevance, computational reliability, and meaningful contributions to decision quality or operational performance.
JIODS places particular emphasis on real-world applications involving complex decisions and operational systems. Applications may include management and business operations, transportation and logistics, supply chain management, manufacturing and industrial engineering, environmental management, energy and sustainability, healthcare operations, infrastructure planning, risk and resilience management, smart cities, digital transformation, and other complex socio-technical environments.
The journal welcomes original research articles, methodological and theoretical studies, computational investigations, algorithmic developments, application-driven research, and high-quality review articles that advance the understanding or practice of intelligent operations and decision sciences. Application-oriented research should provide analytical, methodological, computational, or decision-relevant insights that extend beyond the specific case being investigated.
All submitted manuscripts undergo a rigorous double-blind peer-review process to ensure scientific quality, originality, methodological soundness, and relevance to the journal's scope.
