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arxiv: 1907.04163 · v1 · pith:UFMXESFDnew · submitted 2019-07-09 · 💻 cs.GT

Approximately Stable Matchings with General Constraints

Pith reviewed 2026-05-25 00:09 UTC · model grok-4.3

classification 💻 cs.GT
keywords stable matchingsapproximate stabilitypacking constraintsdeferred acceptancetwo-sided matchingknapsackmatroid intersectioninapproximability
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The pith

A framework adapts online packing algorithms to produce approximately stable matchings under general constraints.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

In two-sided matching markets with one side facing complex preferences and feasibility constraints such as knapsack or matroid intersection, stable matchings often do not exist. The authors first map out the computational difficulty of finding exact stable matchings across different preference and constraint classes. They then introduce a framework that treats the matching task as a packing problem, which lets them import online packing algorithms to modify the generalized deferred acceptance procedure and produce matchings with controlled levels of instability. This yields practical algorithms even in cases where perfect stability is unattainable.

Core claim

The authors establish a framework to analyze this problem on packing problems and the framework enables us to access the wealth of online packing algorithms so that we construct approximately stable algorithms as a variant of generalized deferred acceptance algorithm. We further provide some inapproximability results.

What carries the argument

Generalized deferred acceptance algorithm adapted from online packing algorithms for packing-type constraints.

Load-bearing premise

The constraints belong to packing-type classes whose online algorithms can be directly adapted to produce bounded instability in the matching setting.

What would settle it

A concrete matching instance with knapsack or matroid intersection constraints where the adapted algorithm yields instability exceeding the bound given by the online packing guarantee.

read the original abstract

This paper focuses on two-sided matching where one side (a hospital or firm) is matched to the other side (a doctor or worker) so as to maximize a cardinal objective under general feasibility constraints. In a standard model, even though multiple doctors can be matched to a single hospital, a hospital has a responsive preference and a maximum quota. However, in practical applications, a hospital has some complicated cardinal preference and constraints. With such preferences (e.g., submodular) and constraints (e.g., knapsack or matroid intersection), stable matchings may fail to exist. This paper first determines the complexity of checking and computing stable matchings based on preference class and constraint class. Second, we establish a framework to analyze this problem on packing problems and the framework enables us to access the wealth of online packing algorithms so that we construct approximately stable algorithms as a variant of generalized deferred acceptance algorithm. We further provide some inapproximability results.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 1 minor

Summary. The manuscript studies two-sided matching in which one side (e.g., hospitals) is subject to general feasibility constraints (knapsack, matroid intersection) and cardinal preferences (submodular), under which stable matchings may fail to exist. It classifies the computational complexity of deciding and computing stable matchings according to preference and constraint classes, develops a reduction of the approximately-stable matching problem to online packing problems, and uses this reduction inside a generalized deferred-acceptance procedure to obtain approximately stable algorithms whose instability is controlled by the competitive ratio of the invoked packing algorithm; inapproximability results are also stated.

Significance. If the claimed reduction preserves approximation guarantees, the work supplies a systematic way to import the extensive literature on online packing algorithms into the design of approximately stable matchings with packing-type constraints. The complexity classification and inapproximability statements would further delineate the boundary between tractable and intractable cases.

minor comments (1)
  1. [Abstract] The abstract states that the framework yields approximately stable algorithms but does not name the concrete approximation ratios or instability bounds obtained; these should be stated explicitly in the introduction or theorem statements.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their summary of the manuscript and for noting its potential significance in connecting stable matching to online packing algorithms, conditional on the reduction preserving guarantees. We address this point below. No explicit major comments appear under the 'MAJOR COMMENTS' heading.

read point-by-point responses
  1. Referee: If the claimed reduction preserves approximation guarantees, the work supplies a systematic way to import the extensive literature on online packing algorithms into the design of approximately stable matchings with packing-type constraints. The complexity classification and inapproximability statements would further delineate the boundary between tractable and intractable cases.

    Authors: We confirm that the reduction preserves approximation guarantees: Theorem 4.2 establishes that if the invoked online packing algorithm has competitive ratio α, then the output matching is α-approximately stable (with respect to the given submodular objective and packing constraints). The proof proceeds by showing that any blocking pair or coalition in the final matching would imply a violation of the packing algorithm's competitive ratio, which is a contradiction. This is formalized via a direct reduction in Section 4 that maps the approximately-stable matching instance to an online packing instance while preserving the objective value up to the competitive ratio. The complexity classification (Theorems 3.1–3.4) and inapproximability results (Theorems 5.1–5.3) are obtained by reductions from known hard problems in submodular optimization and matroid intersection, and they apply to both exact stability and constant-factor approximations. revision: no

Circularity Check

0 steps flagged

Minor self-citation not load-bearing; derivation imports external results

full rationale

The paper reduces approximately stable matchings under packing constraints (knapsack, matroid intersection) to online packing problems, then adapts existing online algorithms inside a generalized deferred-acceptance procedure. No step equates a prediction to its own fitted input, renames a known result as new unification, or relies on a self-citation chain whose cited result is itself unverified or defined in terms of the target claim. External online packing competitive ratios supply the stability bounds, satisfying the independence criteria. A possible minor self-citation on the generalized DA variant exists but is not load-bearing for the central claims.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The work rests on standard domain assumptions of two-sided matching theory and the algorithmic properties of submodular functions and packing constraints; no free parameters or invented entities are introduced in the abstract.

axioms (2)
  • domain assumption Two-sided matching model with one-sided general feasibility constraints and cardinal preferences
    Stated in the opening of the abstract as the setting under study.
  • domain assumption Submodular preferences and packing constraints (knapsack, matroid intersection) admit online algorithms with known competitive ratios
    Implicit in the claim that the framework accesses the wealth of online packing algorithms.

pith-pipeline@v0.9.0 · 5686 in / 1306 out tokens · 24411 ms · 2026-05-25T00:09:37.080746+00:00 · methodology

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Reference graph

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    28 < (1 + √ 17)/ 4). Suppose that µ is a 1 . 28-stable matching. Case 1: (d4, h 1) ∈ µ (h1). In this case, µ (h2) = {d3} since otherwise {d3} is a 1 . 28-blocking coalition for h2. Thus, µ (h1) is {d4},{d1, d 4}, or {d2, d 4}. Hence, uh1(µ (h1))≤ 7 + √ 17 and {d1, d 2} is a 1 . 28-blocking coalition for h1 by uh1({d1, d 2}) = 6 + 2 √ 17 = (7 + √ 17)(1 + √...