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Apr 7, 2026¡Figshare
0 cites
OTIMIZAÇÃO DE GAS EM ETHEREUM: ANÁLISE DE OPCODES E ESTRUTURAS DE DADOS

Tiago Ferreira Cavazin

Este artigo analisa estratégias de otimização de gas em Ethereum a partir de duas dimensões principais: o custo dos opcodes da EVM e as escolhas de estruturas de dados em Solidity. A tabela de opcodes da EVM e a evolução do gas schedule mostram que operações de armazenamento e acesso externo, como SSTORE, SLOAD, CALL, BALANCE e EXT*, estão entre as mais caras, especialmente após EIPs como a 2929, que aumentaram o custo de acessos “frios” a contas e slots de storage para refletir melhor seu impacto na execução e na camada de armazenamento. Estudos recentes sobre custos de armazenamento evidenciam que uma escrita em SSTORE pode custar cerca de 22.100 gas para 32 bytes (aprox. 690 gas/byte), enquanto leituras via SLOAD também são significativamente caras, motivando pesquisas sobre técnicas como SSTORE2 e mecanismos para corrigir “overcharge” em leitura/escrita de storage, com ganhos médios de até 30–32% em fees para certos padrões de uso. Boas práticas de otimização de gas em Solidity incluem reduzir o número de acessos a storage movendo valores frequentemente lidos para variáveis em memória, empacotar variáveis em slots de 32 bytes (storage packing), preferir tipos fixos a dinâmicos quando possível, evitar cópias desnecessárias de arrays de storage para memória e desenhar estruturas de dados que minimizem gravações em storage. A literatura e guias de otimização indicam que a escolha entre arrays, mappings, structs e padrões de layout impacta diretamente o custo de execução, especialmente em loops que interagem com storage ou estruturas dinâmicas. Conclui‑se que a otimização de gas em Ethereum é um problema tanto de engenharia de baixo nível, ligado ao custo de opcodes e ao modelo warm/cold de acessos, quanto de design de dados e algoritmos, com implicações econômicas diretas para usuários, protocolos DeFi e estratégias de design de L2s.<br>

Open access
2 source records
Advanced Data Storage Technologies
Parallel Computing and Optimization Techniques
Optimization and Packing Problems
Original source
Feb 20, 2026¡Open MIND
0 cites
Bit-Parallel Maximum Clique via 1024-bit Virtual Registers

AndrĂŠs SebastiĂĄn Pirolo

Stochastic Bit-Parallel Maximum Clique Solver (1024-bit Virtual Register) We introduce a stochastic bit-parallel solver for the Maximum Clique Problem (MCP) based on a 1024-bit virtual register architecture implemented as 16 contiguous uint64_t words in standard C++17, ensuring full portability across 64-bit platforms (x86-64, ARM, RISC-V). Core operations—candidate intersection, population count, and leading-zero detection—execute in exactly 16 instructions per 1024-bit operation. The solver integrates three key components: (i) a co-neighborhood heuristic that identifies high-coreness nodes via O(N²) pairwise popcount over 1024-bit adjacency rows; (ii) a stochastic swarm of independent worker threads; and (iii) greedy clique expansion through iterative bitwise intersection. Exact branch-and-bound solvers (MaxCliqueDyn, MCQ) become computationally intractable on dense random graphs such as G(1024, 0.5), where chromatic coloring bounds lose effectiveness and the search tree grows exponentially, requiring hours of computation on commodity hardware. The proposed method operates specifically within this hard regime, achieving 100% recovery of all 28 planted clique vertices in 153 milliseconds—a setting where exact state-of-the-art methods cannot remain competitive regardless of hardware scaling. Experimental validation was performed on a Qualcomm Snapdragon 8 Gen 2 (8-core ARM) and independently reproduced on Linux x86-64 server hardware. The solver requires no cloud infrastructure and no GPU acceleration. STATEMENT OF PRIOR ART AND LICENSE TERMS (PolyForm Noncommercial Framework) 1. Statement of Prior Art This document constitutes a public disclosure of the stochastic bit-parallel Maximum Clique methodology, including its virtual register architecture, heuristic structure, and execution model.The mathematical and algorithmic concepts are released solely to establish Prior Art and prevent third-party patent claims under 35 U.S.C. § 102 and international equivalents. 2. Software License While the conceptual methods are disclosed defensively, all source code, implementations, binaries, and hardware realizations are not in the public domain and are licensed under the PolyForm Noncommercial License 1.0.0. Permitted (Non-Commercial)• Academic research and experimentation• Peer review and independent verification• Educational and non-profit use• Non-commercial open-source research implementations Condition: Publications must cite the canonical DOI or primary reference. Prohibited (Commercial)• Integration into proprietary software or hardware• Deployment in commercial systems, services, or products• Use in paid tools, platforms, or consulting workflows• Sublicensing or sale of the code or derivatives 3. Commercial Licensing Any commercial use requires explicit written authorization from the author. 4. No Code-Size Threshold (No De Minimis) The PolyForm Noncommercial License imposes no exemptions based on code length, fragment size, or proportion of reuse. Any use—partial or complete—remains fully subject to the license. 5. Anti-Snippet Laundering and Anti-Circumvention Extraction, paraphrasing, refactoring, translation, or reimplementation of any algorithmic component—including bit-parallel structures, heuristics, or execution logic—shall be considered derivative use.Attempts to evade the license through minimal reuse, language changes, functional replication, or modular embedding do not limit its applicability.This interpretation aligns with international good-faith and anti-abuse principles. 6. Presumption of Derivation Any system exhibiting substantial functional or structural similarity, developed after exposure to this work, shall be presumed derivative.The burden of proof for independent creation rests on the alleged infringing party. 7. Knowledge Contamination Exposure to the code, documentation, or technical description constitutes knowledge contamination.Subsequent implementations by exposed parties are not considered clean-room unless supported by contemporaneous evidence of prior independent development. 8. Waiver of Jury Trial To the fullest extent permitted by law, all parties waive the right to a jury trial in disputes arising from this license or related use. 9. Severability and Survival If any provision is deemed unenforceable, the remaining provisions remain in effect.The following provisions survive termination: license scope, noncommercial restrictions, anti-circumvention, presumption of derivation, knowledge contamination, intellectual property ownership, waiver of jury trial, and remedies. 10. Academic Use and Research Freedom The author expressly encourages academic and scientific use of this work. The following activities are permitted on a non-commercial basis: • Research, benchmarking, and experimental validation• Publication of scientific analyses, comparisons, or extensions• Use in university courses, laboratories, and academic projects• Inclusion in research solver portfolios• Independent theoretical or empirical study All academic use must include proper citation to the original work.

Open access
2 source records
Complexity and Algorithms in Graphs
Cloud Computing and Resource Management
Optimization and Packing Problems
Original source
Aug 30, 2024¡Modern Dynamics: Mathematical Progressions.
1 cites
Cross-Chain NFT Marketplaces with Layer Zero and Chain link

Rahul Arulkumaran, Pattabi Rama Rao Thumati, Pavan Kanchi, Lagan Goel ¡ 5 authors

The introduction of non-fungible tokens (NFTs) has revolutionised digital ownership and asset management in the quickly changing environment of blockchain technology. NFTs are a kind of token that cannot be exchanged for another token. On the other hand, as the market for NFTs continues to grow, customers are becoming more and more interested in interoperability across various blockchain networks. Cross-chain non-fungible token markets have been developed as a result of this necessity. These marketplaces make it possible for different blockchain ecosystems to engage in transactions and interactions with one another. LayerZero and Chainlink are two technologies that are very significant in addressing the difficulty of interoperability across different chains.

Open access
Optimization and Packing Problems
Scheduling and Optimization Algorithms
graph theory and CDMA systems
Original source
Jul 11, 2024
0 cites
On rounding algorithms for the 2-edge-connected spanning subgraph problem

Gabriel Morete de Azevedo

A connected loopless graph is 2-edge-connected if it remains connected after the removal of at most one of its edges. Many combinatorial optimization problems seek, for a given graph with costs on its edges, a spanning subgraph satisfying certain connectivity constraints. The minimum 2-edge-connected spanning subgraph problem (2-ECSSP) is a problem of this type. It can be formulated as an integer linear program that selects edges of minimum total cost satisfying the restriction that every cut of the given graph is covered by at least two of the selected edges. This problem is known to be NP-hard. This thesis develops rounding algorithms for three variants of 2-ECSSP, focusing on rounding half-integral solutions of the corresponding linear relaxation. This family of solutions often yields the largest known integrality ratio for various subproblems of 2-ECSSP. The first problem we investigate is the half-integral 2-ECSSP with unrestricted costs. We develop a novel 5/3-rounding that, to the best of our knowledge, is the first one with a factor better than 2. Moreover, we design a reduction scheme, restricting the problem to 4-edge-connected graphs with maximum degree at most five. Then, we study the matching augmentation problem (MAP), a subproblem of 2-ECSSP in which the edge costs are either 0 or 1 and the zero cost edges define a matching. We survey a better-than-2-approximation, obtained in 2022 by Bamas, Drygala, and Svensson, presenting a comprehensive proof of their result and determining an improved factor. Additionally, we address conjectures posed in their work and present computational experiments to support our findings. Finally, we discuss the 2-edge-connected spanning multisubgraph problem (2-ECSMP), a variation of 2-ECSSP in which multiple copies of the same edge can be selected. We survey a recent work by Boyd et al. on a 4/3-rounding for the half-integral 2-ECSMP and leverage their techniques to prove novel decomposition theorems for 4-regular 4-edge-connected graphs. Finally, we pose two conjectures concerning extensions of the decomposition results, suggesting new research directions.

Open access
VLSI and FPGA Design Techniques
Optimization and Packing Problems
Interconnection Networks and Systems
Original source
Oct 30, 2023¡Asia-pacific Journal of Convergent Research Interchange
0 cites
Account Relocation for Optimization Load Balancing in Ethereum Sharding

Yeon Joo Lee, Ik Rae Jeong, Geonta Noh

Existing blockchain system face scalability issues when processing massive amounts of data.These issues primarily arise due to their consensus based block generation methods.Sharding has emerged as a promising on chain solution to enhance the scalability of blockchain.This technology increases throughput by dividing the main network into several sub-networks, called shards, which can process transactions in parallel.However, implementing sharding in blockchain system presents two significant challenges: Cross shard transactions and load imbalance between different shards.Cross shard transaction refers to transactions generated between accounts belonging to different shards.Load imbalance occurs when specifical one shard processes a disproportionately higher transaction load than others.These challenges can lead to increased network delay, confirmation time, latency, and fees due to complicated inter-shard communication, thereby reducing blockchain throughput.To address these challenges, this paper proposes an innovative account relocation scheme.This scheme aims to optimize load balancing in blockchain sharding using a round robin algorithm.To validate the effectiveness of our approach, we utilized a simulator that incorporates real Ethereum data.We then compared the degree of load balancing achieved by our method against existing methods, such as schemes that use no-relocation and random relocation.Our results indicate a significant improvement in load balancing performance compared to previous approaches.

Open access
Scheduling and Optimization Algorithms
Advanced Manufacturing and Logistics Optimization
Optimization and Packing Problems
Original source
Oct 26, 2023
0 cites
NFT minting and owner verification in an NFT E-commerce website

Shashwat, Ravi Shankar Pandey

NFTs or non-fungible tokens are unique digital assets with identifiable characteristics. NFTs can take the form of digital art, GIFs, videos, collectibles, video game merchandise, music, and even tweets. Uniqueness of a digital asset encompasses more than just visual properties, but also factors such as item IDs and hash codes. This means that even though the two NFTs are visually indistinguishable, they have different IDs and codes. In the digital space, these elements are an integral part of an asset&s;s identity as they contain important data about the object&s;s history. The popularity of the Non-Fungible Token (NFT) has grown tremendously since 2020, becoming one of the most popular applications in the Fintech field. However there is still lack of platforms which provide all the functionalities regarding NFTs (including minting, buying and selling) at a single place. This research paper introduces an algorithm for creation of NFTs along with ensuring owner verification which can be used for minting the NFTs in an E-commerce website using the MOTOKO language for creation of canisters consisting the owner id for owner verification and the principal id which serves as a unique token id for the NFT.

Optimization and Packing Problems
Interactive and Immersive Displays
User Authentication and Security Systems
Original source
Jan 1, 2022¡SSRN Electronic Journal
11 cites
A Walk-through of a Simple Zk-STARK Proof

Aleksander Berentsen, Jeremias Lenzi, Remo Nyffenegger

No abstract is available for this record.

Open access
Optimization and Packing Problems
Computational Geometry and Mesh Generation
Advanced Numerical Analysis Techniques
Original source
Jan 1, 2007¡Operational Research
1 cites
Rewriting integer variables into zero-one variables: Some guidelines for the integer quadratic multi-knapsack problem

Dominique Quadri, Éric Soutif

This paper is concerned with the integer quadratic multidimensional knapsack problem (QMKP) where the objective function is separable. Our objective is to determine which expansion technique of the integer variables is the most appropriate to solve (QMKP) to optimality using the upper bound method proposed by Quadri et al. (2007). To the best of our knowledge the upper bound method previously mentioned is the most effective method in the literature concerning (QMKP). This bound is computed by transforming the initial quadratic problem into a 0-1 equivalent piecewise linear formulation and then by establishing the surrogate problem associated. The linearization method consists in using a direct expansion initially suggested by Glover (1975) of the integer variables and in applying a piecewise interpolation to the separable objective function. As the direct expansion results in an increase of the size of the problem, other expansions techniques may be utilized to reduce the number of 0-1 variables so as to make easier the solution to the linearized problem. We will compare theoretically the use in the upper bound process of the direct expansion (I) employed in Quadri et al. (2007) with two other basic expansions, namely: (II) a direct expansion with additional constraints and (III) a binary expansion. We show that expansion (II) provides a bound which value is equal to the one computed by Quadri et al (2007). Conversely, we provide the proof of the non applicability of expansion (III) in the upper bound method. More specifically, we will show that if (III) is used to rewrite the integer variables into 0-1 variables then a linear interpolation can not be applied to transform (QMKP) into an equivalent 0-1 piecewise linear problem.

2 source records
Optimization and Packing Problems
Advanced Manufacturing and Logistics Optimization
Optimization and Search Problems
Original source
Jan 25, 1995
0 cites
4-Move Perfect ZKIP for Some Promise Problems

Kaoru Kurosawa, Wakaha Ogata, Shigeo Tsujii

In this paper, we consider ZKIPs for promise problems. A promise problem is a pair of predicates (Q; R). A Turning machine T solves the promise problem (Q; R) if, for every x satisfying Q(x), machine T halts and it answers &amp;quot;yes&amp;quot; iff R(x). When :Q(x), we do not care what T does. First, we define &amp;quot;promised BPP&amp;quot; which is a promise problem version of BPP. Then, we prove that a promise problem (Q; R) has a 3-move interactive proof system which is black-box simulation zero knowledge if and only if (Q; R) 2 promised BPP. Next, we show a &amp;quot;4-move&amp;quot; perfect ZKIPs (black-box simulation) for a promise problem of Quadratic Residuosity and that of Blum Numbers under no cryptographic assumption.

Optimization and Packing Problems
Advanced Manufacturing and Logistics Optimization
Vehicle Routing Optimization Methods
Original source
Jan 1, 1964¡SIAM Review
538 cites
Heuristic Methods for Location-Allocation Problems

Leon N. Cooper

Previous article Next article Heuristic Methods for Location-Allocation ProblemsLeon CooperLeon Cooperhttps://doi.org/10.1137/1006005PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] Leon Cooper, Location-allocation problems, Operations Res., 11 (1963), 331–343, No. 3 MR0152365 0113.14201 CrossrefISIGoogle Scholar[2] Google Scholar[3] D. H. Lehmer, Teaching combinatorial tricks to a computerProc. Sympos. Appl. Math., Vol. 10, American Mathematical Society, Providence, R.I., 1960, 179–193, Combinatorial Analysis MR0113289 0096.00504 CrossrefGoogle Scholar[4] J. Heller, Some numerical experiments for an $M\times J$ flow shop and its decision-theoretical aspects, Operations Res., 8 (1960), 178–184, No. 2 MR0111626 0092.27910 CrossrefISIGoogle Scholar[5] J. Moshman, The Application of Sequential Estimation To Computer Simulation and Monte Carlo Procedures, J. Association for Computing Machinery, 5 (1958), 0086.11603 CrossrefISIGoogle Scholar[6] A. Wald, Sequential Analysis, John Wiley and Sons, New York, 1952 Google Scholar Previous article Next article FiguresRelatedReferencesCited ByDetails An elliptical cover problem in drone delivery network design and its solution algorithmsEuropean Journal of Operational Research, Vol. 304, No. 3 | 1 Feb 2023 Cross Ref Two lower-bounding algorithms for the p-center problem in an areaComputational Urban Science, Vol. 2, No. 1 | 24 January 2022 Cross Ref Optimal planar facility location with dense demands along a curveJournal of the Operational Research Society, Vol. 73, No. 8 | 8 May 2021 Cross Ref A continuous location and maintenance routing problem for offshore wind farms: Mathematical models and hybrid methodsComputers & Operations Research, Vol. 144 | 1 Aug 2022 Cross Ref Spatial autocorrelation informed approaches to solving location–allocation problemsSpatial Statistics, Vol. 50 | 1 Aug 2022 Cross Ref Electric vehicle charging stations emplacement using genetic algorithms and 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