Abstract: This paper proposes a novel multi-objective grey wolf optimizer based on decomposition and adaptive constraint scaling (D-ACSMOGWO) to address the shortcomings of existing algorithms in ...

1 Department of Quantitative Methods, University of Sousse, Sousse, Tunisia 2 Department of Quantitative Methods, College of Business, King Faisal University, Al-Ahsa, Saudi Arabia Introduction: ...

Abstract: Expensive multi-objective binary optimization problems frequently emerge in real-world applications, where evaluating a single solution incurs significant computational or physical costs.

Researchers have developed a novel multi-constraint optimization method that significantly improves the efficiency of reinforcement learning in complex environments. This new algorithm, called ...

1 China Railway 22nd Bureau Group Real Estate Development Co., Ltd., Beijing, China 2 School of Civil Engineering, North China University of Technology, Beijing, China Balancing the relationship ...

As biological data volume continues to grow, sequence-based AI is poised to become the dominant discovery layer across pharma ...

New, Canada-wide evidence from a late-2025 pulse survey of 648 acute care stakeholders-plus a 2026-2030 buyer roadmap on interoperability-as-a-procurement-gate, data sovereignty, and tightening ...

How Promise Theory and integrity scoring enable autonomous AI agents to govern themselves at enterprise scale.

Another January 30 arrives . Another anniversary of Agenda 2063; Africa rsquo;s most ambitious collective promise .

Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...