About the Journal

Decision Intelligence and Complex Computing is an international, peer-reviewed, open-access journal dedicated to research at the intersection of decision intelligence, complex systems, and advanced computational methods. The journal publishes original contributions that advance how complex decisions are formulated, modelled, analysed, supported, and evaluated in environments characterized by uncertainty, multiple objectives, interconnected processes, dynamic behaviour, and large or heterogeneous data.

The journal is founded on the view that many contemporary decision problems cannot be adequately addressed by isolated analytical or computational techniques. Effective decision intelligence increasingly requires the integration of mathematical and computational models, artificial intelligence, optimization, data analytics, domain knowledge, and human judgment. Decision Intelligence and Complex Computing therefore provides a multidisciplinary platform for research that connects methodological innovation with the structure and complexity of real decision problems.

The journal welcomes theoretical, methodological, computational, empirical, and application-oriented research that contributes to the development of more intelligent, robust, explainable, and effective decision processes. Relevant contributions may originate from decision science, operations research, artificial intelligence, computational intelligence, computer science, engineering, economics, finance, management science, environmental science, and other disciplines concerned with complex decision-making.

Particular emphasis is placed on research addressing complexity rather than computational sophistication alone. This includes decisions involving uncertainty and risk, conflicting objectives, interacting decision-makers, nonlinear or dynamic systems, incomplete information, large-scale computational structures, competing stakeholder interests, and interconnected technological, economic, environmental, or social processes.

Decision Intelligence and Complex Computing encourages research that moves beyond the routine application of established algorithms or computational tools. Manuscripts are expected to provide a clearly identifiable contribution through methodological advancement, theoretical development, computational innovation, rigorous empirical evidence, new decision insight, or a meaningful integration of methods and disciplines. Application-oriented studies should generate findings or methodological insights that extend beyond the immediate case under investigation.

The journal covers a broad range of decision contexts, including business and management, finance and investment, engineering and manufacturing, logistics and supply chains, energy and sustainability, environmental and climate systems, infrastructure, healthcare, public policy, and intelligent and autonomous systems. Interdisciplinary studies connecting several of these domains are particularly encouraged.

Through this focus, Decision Intelligence and Complex Computing seeks to establish a distinctive international forum connecting intelligent analysis, computational complexity, and decision action. Its objective is not only to develop increasingly powerful computational methods, but also to advance the scientific understanding of how such methods can produce better decisions in complex real-world systems.

General Guidelines for Authors

Decision Intelligence and Complex Computing considers the following principal manuscript types:

• Original Research Articles
• Review Articles
• Methodological Papers
• Application and Empirical Studies
• Short Communications
• Perspective and Emerging Research Articles

Original research articles should clearly establish the decision problem or scientific question, position the study within the relevant literature, identify the research gap and contribution, describe the theoretical or methodological foundations, and provide rigorous analytical, computational, experimental, simulation-based, or empirical validation where appropriate.

Methodological papers should introduce or substantially advance models, algorithms, frameworks, analytical procedures, or computational approaches relevant to complex decision-making. The contribution should be demonstrated through appropriate theoretical analysis, benchmarking, experimentation, or substantive applications.

Application and empirical studies are welcome when they provide more than a routine implementation of established methods. Such manuscripts should demonstrate methodological relevance, transferable decision insights, substantive empirical findings, or evidence that advances understanding beyond a single organization, dataset, or case.

Review articles should provide critical and structured syntheses of established or emerging research areas, identify limitations and unresolved questions in the existing literature, and develop a clear agenda for future research.

Short communications and perspective articles may present significant emerging ideas, novel conceptual developments, timely methodological insights, or promising new directions relevant to decision intelligence and complex computing.

The journal does not prescribe a fixed manuscript length. Contributions should be sufficiently detailed to ensure scientific reproducibility, methodological transparency, and rigorous interpretation of results while remaining focused on the stated research contribution.

Extended versions of previously published conference papers may be considered when they contain substantial new scientific content. Authors must clearly identify and cite the earlier publication and demonstrate the additional contribution of the submitted manuscript, which may include new theoretical results, methodological developments, substantially extended experiments, additional datasets or applications, deeper analysis, or materially expanded scientific conclusions.