cuGenOpt: GPU-Accelerated General-Purpose Metaheuristic Framework for Combinatorial Optimization

arXiv 2603.19163·medium signal

cuGenOpt (arXiv:2603.19163) introduces a CUDA framework that parallelizes metaheuristic algorithms (simulated annealing, genetic algorithms) across GPU threads for combinatorial optimization in logistics, scheduling, and resource allocation. The framework targets the generality-performance-scalability trade-off that hampers existing approaches, providing a drop-in accelerator for NP-hard scheduling subproblems. Applicable to multi-agent orchestration systems with complex task scheduling requirements.