Why AI‑Driven Inventory Optimization Frameworks Are Replacing Traditional Planning Models

The shift toward AI-driven decision frameworks is not simply a technological trend but a fundamental necessity for life ...
IEEE

N(CO) 2: Neural Combinatorial Optimization with Chance Constraints to Solve Stochastic Orienteering

Abstract: Neural combinatorial optimization (NCO) offers a promising alternative to traditional heuristic-based methods for solving complex graph optimization problems by proposing to learn heuristics ...
AlphaGalileo

Optimizing RNA Design with AI and an Ising Machine: Encoding Matters

RNA design is central to next-generation therapeutics, yet identifying sequences that reliably fold into desired structures ...
IEEE

Alternating Refined Constraint Method: A Multi-Objective Solution Approach for Energy System Optimization

Abstract: This paper proposes an alternating refined constraint method (ARCM) for solving multi-objective optimization problems (MOPs) in energy systems. Through a two-stage solution mechanism, ARCM ...
Tech Xplore

Researchers discover a smarter way to solve vehicle routing problems using adaptive swarm learning

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...