Robopol Refined: A Universal Guided Search Engine for Combinatorial Optimization
Year: 2026
Type: preprint
Abstract: Robopol Refined is a reusable guided search engine for combinatorial optimization. The paper presents the method as a universal framework built around a generic search core and problem-specific adapters. The core handles candidate management, beam-style selection, repeated improvement, perturbation, deterministic parallel search, and diagnostics, while adapters supply scoring, move generation, guidance edges, local search, and domain-specific validity logic. The document focuses on the public architecture and positioning of Robopol Refined across routing, scheduling, packing, graph, assignment, and subset-selection problems. It intentionally avoids disclosing proprietary implementation details such as exact edge ranking formulas, candidate scoring rules, perturbation schedules, parameter recipes, or benchmark-specific tuning.
Author: Polak, Robert
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7161596934
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