Pith. sign in

REVIEW 1 major objections 23 references

A sequence space over a preordered base yields total preorders on fuzzy numbers by sequential lexicographic tie resolution.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

T0 review · grok-4.3

2026-06-30 01:22 UTC pith:NYJYTJAA

load-bearing objection The paper supplies a sequence-space lex framework that unifies fuzzy number rankings under one total preorder construction. the 1 major comments →

arxiv 2606.28451 v1 pith:NYJYTJAA submitted 2026-06-26 math.GM

Sequential ordering relations with application to fuzzy numbers

classification math.GM
keywords sequential orderingfuzzy numberstotal preorderlexicographic orderadmissible ordersranking methodsfuzzy set theorytie resolution
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper constructs a generalized sequential ordering framework to rank fuzzy numbers, which remain incomparable under partial orders such as the Klir-Yuan relation on alpha-cuts. It defines a sequence space over any totally preordered base and uses a flexible lexicographic mechanism to resolve ties one position at a time. This construction is shown to produce total preorders in general and total orders when the sequences are injective, while remaining compatible with admissible orders and recovering many existing ranking methods as special cases. A sympathetic reader cares because the method avoids the information loss of defuzzification yet still supplies a total ranking without the rigid algebraic constraints that can conflict with intuition.

Core claim

By establishing a sequence space over a totally preordered base space, the authors construct a flexible lexicographical structure that sequentially resolves ties. They prove that this framework yields total preorders and, under injectivity conditions, total orders. The sequential orders are compatible with admissibility, and the same construction supplies a unified umbrella that encompasses and generalizes existing ranking techniques for fuzzy numbers.

What carries the argument

The sequence-space construction over a totally preordered base with sequential tie resolution, functioning as a generalized lexicographic order that produces totality while preserving the base preorder.

Load-bearing premise

The base space admits a total preorder and the sequence-space construction with sequential tie resolution preserves the required preorder properties without introducing inconsistencies.

What would settle it

A concrete pair of fuzzy numbers whose alpha-cut sequences are comparable under the base preorder yet produce a cycle or incomparability when the sequential lexicographic rule is applied.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • The framework produces a total preorder on the set of fuzzy numbers for any choice of totally preordered base.
  • When the mapping from fuzzy numbers to sequences is injective, the resulting relation is a total order.
  • The constructed orders are compatible with the algebraic conditions required for admissibility.
  • Many classical ranking methods for fuzzy numbers arise as special cases inside the same sequence-space construction.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same sequence-space template could be applied to other partially ordered objects such as intervals or type-2 fuzzy sets by choosing an appropriate base preorder.
  • Different choices of the base preorder and sequence length would generate families of rankings whose discrimination power can be compared directly on benchmark sets of fuzzy numbers.
  • The framework suggests a way to quantify information retention by measuring how many ties survive at each sequence position before a decision is reached.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

1 major / 0 minor

Summary. The manuscript introduces a sequential ordering framework for ranking fuzzy numbers by constructing a sequence space over a totally preordered base and applying a flexible lexicographic tie-resolution procedure. It claims to prove that the resulting relations are total preorders (and total orders under injectivity conditions), to establish compatibility with the notion of admissibility, and to show that the framework unifies and generalizes existing ranking methods while avoiding both defuzzification losses and overly restrictive algebraic constraints.

Significance. If the central claims hold, the work supplies a systematic order-theoretic umbrella for total preorders on fuzzy numbers that is more flexible than classical admissible orders. However, the described construction is the standard lexicographic extension of a total preorder to the sequence space, a fact already known to guarantee totality (and injectivity-implied antisymmetry) in order theory; this reduces the novelty of the contribution to the specific application and the admissibility-compatibility analysis.

major comments (1)
  1. [Abstract] The abstract asserts proofs of totality, injectivity conditions for total orders, and admissibility compatibility, yet the provided text supplies no derivation details, explicit definitions of the sequence-space ordering, or verification steps; without these, the load-bearing claims cannot be assessed for correctness or for whether they reduce to the standard lexicographic fact.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the detailed report on our manuscript. The single major comment addresses the abstract's level of detail regarding proofs and definitions. We respond point by point below and indicate where revisions can be made.

read point-by-point responses
  1. Referee: [Abstract] The abstract asserts proofs of totality, injectivity conditions for total orders, and admissibility compatibility, yet the provided text supplies no derivation details, explicit definitions of the sequence-space ordering, or verification steps; without these, the load-bearing claims cannot be assessed for correctness or for whether they reduce to the standard lexicographic fact.

    Authors: The abstract is intended as a high-level summary and therefore omits full derivations, which appear in the body of the manuscript. Section 2 explicitly constructs the sequence space over a totally preordered base; Section 3 defines the flexible lexicographic tie-resolution; and Section 4 supplies the proofs that the resulting relations are total preorders (with injectivity yielding total orders). Admissibility compatibility is verified in Section 5 via direct comparison with the admissibility axioms. We are willing to revise the abstract to include a one-sentence outline of the construction and to cite the relevant sections. While the core mechanism is indeed a lexicographic extension of a total preorder, the manuscript's contribution consists in the specific application to fuzzy numbers, the unification of disparate ranking methods under a single order-theoretic umbrella, and the admissibility analysis that avoids both defuzzification and overly restrictive algebraic constraints; these elements are not standard in the existing literature. revision: partial

Circularity Check

0 steps flagged

No significant circularity; standard order-theoretic construction

full rationale

The paper defines a sequence space over a totally preordered base and equips it with a sequential (lexicographic) tie-resolution rule. The claimed results—yielding total preorders, total orders under injectivity, and compatibility with admissibility—follow directly from the explicit definition of the order relation and the standard properties of lexicographic products on preordered sets. No equations or proofs reduce a derived claim to a fitted parameter, a self-referential definition, or a load-bearing self-citation whose content is itself unverified. The generalization of existing ranking methods is presented as an application of the new framework rather than a renaming or smuggling of prior ansatzes. The derivation is therefore self-contained against external order-theoretic benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

The central claim rests on the introduction of the sequence-space construction and standard assumptions from order theory; no free parameters are mentioned.

axioms (2)
  • domain assumption The base space is totally preordered
    Invoked to construct the sequence space and lexicographic structure.
  • ad hoc to paper Sequential lexicographic resolution on sequences produces a total preorder
    Core property asserted for the new framework.
invented entities (1)
  • sequential ordering framework no independent evidence
    purpose: To construct total preorders on fuzzy numbers via sequence spaces over a preordered base
    New structure introduced to overcome limitations of partial orders and defuzzification methods

pith-pipeline@v0.9.1-grok · 5738 in / 1360 out tokens · 35149 ms · 2026-06-30T01:22:23.348814+00:00 · methodology

0 comments
read the original abstract

The ranking of fuzzy numbers has become a challenging task in fuzzy set theory due to their complex, multi-dimensional nature. While the Klir-Yuan partial order provides a natural term-wise comparison of $\alpha$-cuts, it often leaves many fuzzy numbers incomparable. To address this, various ranking methods have been developed to construct total preorders between them. However, many classical approaches suffer from significant information loss as they imply a defuzzification process. On the other hand, approaches such as admissible orders allow defining total orders, but at the expense of imposing strict algebraic rules that may contradict human intuition. In this study, we introduce a generalized sequential ordering framework to overcome these limitations. By establishing a sequence space over a totally preordered base space, we construct a flexible lexicographical structure that sequentially resolves ties. We prove that this framework yields total preorders and, under injectivity conditions, total orders. Furthermore, we analyze the compatibility of these sequential orders with the notion of admissibility. We also show that our proposed framework provides a unified mathematical umbrella that encompasses and generalizes existing ranking techniques, offering highly discriminative ordering relations for fuzzy numbers and beyond.

Figures

Figures reproduced from arXiv: 2606.28451 by Antonio Francisco, Diego, Garc\'ia-Zamora, Rold\'an L\'opez de Hierro.

Figure 1
Figure 1. Figure 1: Comparison of A = (1, 4, 5, 8) and B = (2, 3, 6, 7). Let us overcome this incomparability by employing two distinct sequential approaches. First, we utilize an admissible order based on α-cuts. Concretely, we will utilize the Lexicographical 2 interval order (which prioritizes the upper bound) to compare the supports of the trapezoidal fuzzy numbers and, if tied, we will compare the cores. Since A0 = [1, 8… view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

23 extracted references

  1. [1]

    Abbasbandy and T

    S. Abbasbandy and T. Hajjari. A new approach for ranking of trapezoidal fuzzy numbers. Computers & Mathematics with Applications, 57(3):413–419, 2009

  2. [2]

    Alfonso, A.F

    G. Alfonso, A.F. Roldán López de Hierro, and C. Roldán. A fuzzy regression model based on finite fuzzy numbers and its application to real-world financial data.Journal of Computational and Applied Mathematics, 318:47–58, 2017

  3. [3]

    Richard E Bellman and Lotfi A. Zadeh. Decision-making in a fuzzy environment.Man- agement Science, 17(4):B–141, 1970

  4. [4]

    Generation of linear orders for intervals by means of aggregation functions.Fuzzy Sets and Systems, 220:69–77, 2013

    Humberto Bustince, Javier Fernández, Anna Kolesárová, and Radko Mesiar. Generation of linear orders for intervals by means of aggregation functions.Fuzzy Sets and Systems, 220:69–77, 2013

  5. [5]

    Fuzzy multiple criteria decision making: Recent developments.Fuzzy sets and systems, 78(2):139–153, 1996

    Christer Carlsson and Robert Fullér. Fuzzy multiple criteria decision making: Recent developments.Fuzzy sets and systems, 78(2):139–153, 1996

  6. [6]

    Academic press, 1980

    Didier J Dubois.Fuzzy sets and systems: theory and applications, volume 144. Academic press, 1980

  7. [7]

    The deck of cards method to build interpretable fuzzy sets in decision-making.European Journal of Operational Research, 319(1):246–262, 2024

    Diego García-Zamora, Bapi Dutta, José Rui Figueira, and Luis Martínez. The deck of cards method to build interpretable fuzzy sets in decision-making.European Journal of Operational Research, 319(1):246–262, 2024

  8. [8]

    Diego García-Zamora, Anderson Cruz, Fernando Neres, Antonio Francisco Roldán López de Hierro, Regivan H. N. Santiago, and Humberto Bustince. On the admissibility of the alpha-order for fuzzy numbers.Computational and Applied Mathematics, 43(6), August 2024. 17

  9. [9]

    Santiago, Anto- nio Francisco Roldán López de Hierro, Rui Paiva, Graçaliz

    Diego García-Zamora, Anderson Cruz, Fernando Neres, Regivan H.N. Santiago, Anto- nio Francisco Roldán López de Hierro, Rui Paiva, Graçaliz. P. Dimuro, Luis Martínez, Benjamín Bedregal, and Humberto Bustince. Admissible OWA operators for fuzzy num- bers.Fuzzy Sets and Systems, 480:108863, 2024

  10. [10]

    A note on the admissibility of the centroid-based preorder for fuzzy numbers

    Diego García-Zamora, Antonio Francisco Roldán López de Hierro, and Humberto Bustince. A note on the admissibility of the centroid-based preorder for fuzzy numbers. Computational and Applied Mathematics, 45(4), December 2025

  11. [11]

    Springer Science & Business Media, 2008

    Cengiz Kahraman.Fuzzy multi-criteria decision making: theory and applications with recent developments, volume 16. Springer Science & Business Media, 2008

  12. [12]

    Klir and Bo Yuan.Fuzzy Sets and Fuzzy Logic: Theory and Applications

    George J. Klir and Bo Yuan.Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1995

  13. [13]

    Kulisch and Willard L

    Ulrich W. Kulisch and Willard L. Miranker.Computer arithmetic in theory and practice. Academic Press, 1981

  14. [14]

    Fernando Neres, Regivan H. N. Santiago, Antonio Francisco Roldán López de Hierro, Anderson Cruz, Zdenko Takáč, Javier Fernandez, and Humberto Bustince. The alpha- ordering for a wide class of fuzzy sets of the real line: the particular case of fuzzy numbers. Computational and Applied Mathematics, 43(12), 2024

  15. [15]

    Some applications of thestudyoftheimageofafuzzynumber: Countablefuzzynumbers, operations, regression and a specificity-type ordering.Fuzzy Sets and Systems, 257:204–216, 2014

    Antonio Roldán, Juan Martínez-Moreno, and Concepción Roldán. Some applications of thestudyoftheimageofafuzzynumber: Countablefuzzynumbers, operations, regression and a specificity-type ordering.Fuzzy Sets and Systems, 257:204–216, 2014

  16. [16]

    Total orderings defined on the set of all fuzzy numbers

    Wei Wang and Zhenyuan Wang. Total orderings defined on the set of all fuzzy numbers. Fuzzy Sets and Systems, 243:131–141, 2014. Theme: Fuzzy Intervals and Applications

  17. [17]

    Wang and E.E

    X. Wang and E.E. Kerre. Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets and Systems, 118(3):375–385, 2001

  18. [18]

    On the centroids of fuzzy numbers.Fuzzy Sets and Systems, 157(7):919–926, 2006

    Ying-Ming Wang, Jian-Bo Yang, Dong-Ling Xu, and Kwai-Sang Chin. On the centroids of fuzzy numbers.Fuzzy Sets and Systems, 157(7):919–926, 2006

  19. [19]

    Ronald R. Yager. Ranking fuzzy subsets over the unit interval. InProceedings of the Control and Decision Conference (CDC), pages 1435–1437, 1978

  20. [20]

    Lotfi A. Zadeh. Fuzzy sets.Information Control, 8(3):338–353, 1965

  21. [21]

    Lotfi A. Zadeh. The concept of a linguistic variable and its application to approximate reasoning-I.Information Sciences, 8(3):199–249, 1975

  22. [22]

    Springer Science & Business Media, 2012

    Hans-Jürgen Zimmermann.Fuzzy sets, decision making, and expert systems, volume 10. Springer Science & Business Media, 2012

  23. [23]

    Admissible orders on fuzzy numbers.IEEE Transactions on Fuzzy Systems, 30(11):4788–4799, November 2022

    Nicolas Zumelzu, Benjamin Bedregal, Edmundo Mansilla, Humberto Bustince, and Roberto Diaz. Admissible orders on fuzzy numbers.IEEE Transactions on Fuzzy Systems, 30(11):4788–4799, November 2022. 18