Methodological Innovations in Operations Research for Sustainable Resource Allocation

Dear Colleagues,

Resource allocation problems are central to many societal and organizational problems, including healthcare or energy systems, logistics or manufacturing, and sustainability. Over the decades, the Operational Research (OR) community has made considerable contributions to the application of optimization, simulation, and Multicriteria Decision Making (MCDM).

Sustainable resource allocation demands decisions that balance environmental integrity, social equity, economic viability, and population health—often under deep uncertainty, tight public budgets, heterogeneous needs, and sparse data. Existing approaches may lack predictive power and transparency across these dimensions. To advance practice toward the Sustainable Development Goals, decision-makers require methods that are both evidence-driven and participatory, ensuring that the priorities of families and communities are explicitly represented.

This Special Issue welcomes contributions that extend classical operations research—optimization, simulation, and multicriteria decision-making—with data-driven paradigms in machine learning and AI, including robust and stochastic optimization, causal and Bayesian inference, interpretable and fair AI, and methods that integrate life-cycle and systems perspectives.

We particularly welcome frameworks that reconcile trade-offs across environmental (e.g., emissions, biodiversity), social (e.g., access, equity), economic (e.g., affordability, resilience), and health outcomes; that support transparent, auditable decisions; and that embed stakeholder engagement throughout the analytic pipeline. By uniting theory, methods, and applications, this Special Issue positions interdisciplinary, applied OR at the core of sustainability science and outlines a practical, scalable pathway to more effective, robust, and accountable decisions in sustainable resource allocation.

We welcome the submission of original research articles and reviews. The scope of this Special Issue includes, but is not limited to, optimization, simulation, multicriteria analysis, machine learning, and cost–benefit analysis with regard to the following:

• Cutting-edge methodologies that support sustainable resource allocation decisions, such as optimization techniques, simulation, machine learning and hybrid approaches.
• MCDM combined with optimization or computational simulation to address complex trade-offs in multidimensional sustainable decisions.
• MCDM combined with grey systems-based approaches to address problems with poor or missing data in this scenario.
• The use of OR approaches, including new technologies including AI, big data and digital twins.
• New theories and methodologies dealing with uncertainty, risk, and dynamic environments to deal with this complex situation.
• Applications from any domain (including but not limited to healthcare, logistics, energy, sustainability, manufacturing, public policy, etc.) related to the call.
• The comparison and benchmarking of methods for the real world in sustainable resource allocation.
• Multicriteria Decision support combined with scenario planning (deterministic and non-deterministic) to address this problem.
• Case studies, survey and practical implementations that demonstrate the impact of methodological contributions.

We look forward to receiving your contributions. 

Prof. Dr. José Geraldo Vidal Vieira
Dr. Tiago Sigahi
Dr. Mateus Pereira Martin
Guest Editors

Manuscript Submission Information

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• resource allocation
• sustainable resource allocation
• deprivation community
• slums
• operational research (OR)
• multi-criteria decision making (MCDM)
• portfolio analysis
• cost-benefit analysis
• machine learning
• simulation
• community