Anupam Yadav

About

Dr. Anupam Yadav has done PhD from Indian Institute of Technology Roorkee. His area of research is Computational Optimization, Soft Computing Techniques and their Applications

Employment

• National Institute of Technology Uttarakhand Asst. Professor
  2014 - 2018

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (42)

• An interpretability framework for Ant Colony Optimization in continuous domains
  Swarm and Evolutionary Computation 2026 DOI: 10.1016/j.swevo.2026.102449
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• Chaotic strategies-enhanced artificial electric field algorithm for combinatorial feature selection
  Journal of Combinatorial Optimization 2026 DOI: 10.1007/s10878-026-01409-4
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• A binary multi-objective optimization algorithm for large-scale feature selection problems
  Evolving Systems 2026 DOI: 10.1007/s12530-025-09767-w
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• An Ensemble of Swarm‐Based Evolutionary Learning Strategies for UAV Path‐Planning Problem
  Concurrency and Computation: Practice and Experience 2026 DOI: 10.1002/cpe.70536
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• An explainable reconfiguration-based artificial electric field algorithm for industrial and reliability-redundancy allocation problems
  Evolving Systems 2026 DOI: 10.1007/s12530-026-09857-3
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• Advancements in multimodal differential evolution: a comprehensive review and future perspectives
  Artificial Intelligence Review 2025 DOI: 10.1007/s10462-025-11314-7
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• Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies
  2025 DOI: 10.1145/3712255.3726658
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• EAEFA-R: Multiple learning-based ensemble artificial electric field algorithm for global optimization
  Knowledge-Based Systems 2025 DOI: 10.1016/j.knosys.2025.113453
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• U-AEFA: Online and offline learning-based unified artificial electric field algorithm for real parameter optimization
  Knowledge-Based Systems 2024 DOI: 10.1016/j.knosys.2024.112636
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• An adaptive artificial electric field algorithm for continuous optimization problems
  Expert Systems 2023 DOI: 10.1111/exsy.13380
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