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Held–Karp algorithm

An exact dynamic-programming algorithm for the traveling-salesman problem that stores the cheapest start-to-end path through each subset of cities, reducing tour enumeration to exponential subset recurrence.

Version
v1 · 2026-09-08 · History
Domain-specific #
4850
Origin domain
algorithms
Subdomain
exact traveling salesman methods
Aliases
Bellman–Held–Karp algorithm, Bellman-Held-Karp algorithm

Core Idea

The Bellman–Held–Karp algorithm solves TSP exactly by computing the minimum cost of a path from a fixed start through every vertex in a subset and ending at a specified vertex, then closing the best full path into a tour. Optimal substructure lets a state for subset S and endpoint j minimize over predecessor k in S; subset-size order ensures predecessor states exist, and a final edge to the start closes the cycle. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.

Scope of Application

Held–Karp algorithm belongs to algorithms and is useful where the analyst can specify a weighted complete directed or undirected graph, a designated start vertex, subsets of remaining vertices, endpoint-indexed path costs, recurrence states and tour reconstruction, then evaluate each dynamic-program state records exactly one visited subset and terminal vertex, the recurrence considers every possible predecessor, and the final minimization closes a Hamiltonian tour. The scope is broad within that domain but bounded by the need for each dynamic-program state records exactly one visited subset and terminal vertex, the recurrence considers every possible predecessor, and the final minimization closes a Hamiltonian tour. The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.

Clarity

The abstraction clarifies a crowded vocabulary by making each dynamic-program state records exactly one visited subset and terminal vertex, the recurrence considers every possible predecessor, and the final minimization closes a Hamiltonian tour the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test. A bare label is insufficient because the name Held–Karp algorithm can be used for a formal identity, an implementation, or a neighboring result unless carrier and convention are stated.

Manages Complexity

Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Held–Karp algorithm. Held–Karp algorithm compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.

Abstract Reasoning

  1. Identify the carrier. State what the elements, states, objects, or observations are: a weighted complete directed or undirected graph, a designated start vertex, subsets of remaining vertices, endpoint-indexed path costs, recurrence states and tour reconstruction. Reject examples whose alleged carrier belongs to a different problem. 2. Lock the constitutive rule. Express each dynamic-program state records exactly one visited subset and terminal vertex, the recurrence considers every possible predecessor, and the final minimization closes a Hamiltonian tour independently of one notation or implementation.

Knowledge Transfer

Knowledge transfers strongly among subfields of algorithms because they reuse a weighted complete directed or undirected graph, a designated start vertex, subsets of remaining vertices, endpoint-indexed path costs, recurrence states and tour reconstruction, Optimal substructure lets a state for subset S and endpoint j minimize over predecessor k in S; subset-size order ensures predecessor states exist, and a final edge to the start closes the cycle., and type the carrier, state every parameter and convention in the definition, test that each dynamic-program state records exactly one visited subset and terminal vertex, the recurrence considers every possible predecessor, and the final minimization closes a Hamiltonian tour, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.

Relationships to Other Abstractions

Local relationship map for Held–Karp algorithmParents appear above the current abstraction, mutual partners to the right, and children below. Node labels state whether each abstraction is prime or domain-specific; colors identify relation types.Held–Karp algorithmDOMAINPrime abstraction: Algorithm — is a kind ofAlgorithmPRIME

Current abstraction Held–Karp algorithm Domain-specific

Parents (1) — more general patterns this builds on

  • Held–Karp algorithm is a kind of Algorithm Prime

    The proposed strict upward parent is prime:algorithm.

Hierarchy paths (2) — routes to 2 parentless roots

Neighborhood in Abstraction Space

Held–Karp algorithm sits in a moderately populated region (48th percentile for distinctiveness): it has near-neighbors but no dense thicket of look-alikes.

Family — Graph Connectivity & Network Measures (31 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-09-08