hubecall | Tag : economic and social sciences https://hubecall.com/tag/economic-and-social-sciences Derniers appels à publications avec le tag 'economic and social sciences'. Thu, 13 Aug 2026 04:31:20 GMT https://validator.w3.org/feed/docs/rss2.html https://github.com/jpmonette/feed fr hubecall | Tag : economic and social sciences https://hubecall.com/public/favicon/android-chrome-96x96.png https://hubecall.com/tag/economic-and-social-sciences hubecall © 2026 <![CDATA[Multiple Objective Programming and Goal Programming: Artificial Intelligence for Decision Making in Economic and Social Sciences]]> https://hubecall.com/call/springer-multiple-objective-programming-and-goal-programming-artificial-intelligence-for-decision-making-in-economic-and-social-sciences springer-multiple-objective-programming-and-goal-programming-artificial-intelligence-for-decision-making-in-economic-and-social-sciences Tue, 11 Aug 2026 21:25:02 GMT

Matteo Rocca, University of Insubria

Davide La Torre, Skema Business School

Constantin Zopounidis, Technical University of Crete

This special issue aims to publish selected papers presented during the 16th International Conference on Multiple Objective Programming and Goal Programming (MOPGP'25) that will be held on 1–3 July 2025, in Varese, Italy. Contributions arising from papers presented at the conference should be substantially extended and cite the conference paper where appropriate. The special issue will also consider papers not presented during the conference. Original and unpublished work not currently under consideration in any other journal is welcome.

The intersection of Multiple Objective Optimization (MOP), Goal Programming (GP), and Artificial Intelligence (AI) creates a robust framework for addressing complex decision-making challenges in Economic and Social Sciences. MOP provides structured methods to evaluate and prioritize conflicting objectives, while GP helps setting specific goals to be achieved by the decision maker. AI leverages data analytics and machine learning to process large datasets, revealing insights that improve the accuracy and the robustness of decision models and predictions.

The scientific quality of the contributions is the main criterion in the selection process.

Potential topics

  • Advancements in Multiple Objective Programming Techniques
  • Goal Programming Techniques and Formulations
  • Goal Programming Approaches in Public Policy
  • AI-Enhanced Decision Support Systems for Resource Allocation
  • Data-Driven Methods in Economic and Social Decision-Making
  • Integrating Machine Learning with MOP
  • Multicriteria Deep Learning
  • Applications of MOP and GP in Sustainable Development
  • Real-Time Decision-Making Frameworks Using AI
  • Comparative Studies of MOP and GP in Various Contexts
  • Multi-Criteria Decision Analysis in Sustainable Economics
  • Multiple Criteria Decision Making in Environmental Economics
  • Optimization Models for Social Welfare
  • Behavioural Insights in Multi-Objective Decision-Making
  • Metaheuristics and Computational Methods in MOP
  • MOP and MCDM in AI applications
  • Innovative Applications to Economic and Social Sciences

Timeline

  • June 30, 2027: Submission deadline
]]> Annals of Operations Research (SPRINGER)