Researchers have developed KAYROS, an open-source solver designed for complex vehicle routing problems where travel times vary based on departure and each route's dispatch time is a decision variable. This solver is notable for being the first to offer both anytime capabilities, providing improving solutions rapidly, and exactness, with verifiable certificates of optimality for problems involving rich, piecewise-linear travel-time functions. KAYROS builds upon existing solvers by incorporating an open LP backend, anytime and warm-start behavior, and exact treatment of stepwise travel times. The accompanying report also introduces Poryos2026, a new benchmark collection derived from OpenStreetMap data, featuring 1,080 instances of various vehicle routing problem types with controlled demands and congestion, each with a validated best-known solution. AI
IMPACT This solver could advance optimization techniques in logistics and operations research, potentially impacting AI applications in supply chain management and autonomous systems.
RANK_REASON The cluster describes a new open-source solver and benchmark for a specific type of optimization problem, detailed in a technical report. [lever_c_demoted from research: ic=1 ai=0.7]
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