Heuristics for Ethereum Block Building With Semantic Interactions

Abstract

Ethereum block building has traditionally been approached using greedy algorithms that prioritize transactions with the highest fee per unit of gas. This work proposes an alternative that considers semantic interactions among transactions and operational constraints to define the utility of transaction combinations. Through a utility model that assigns bonuses and penalties to pairs and triples of transactions, we design algorithms capable of constructing blocks more valuable than those obtained by traditional methods. In experiments with 1,000 real transactions extracted from the network, two algorithms were implemented and evaluated, both grounded in a formulation inspired by job scheduling theory: a classic greedy baseline and the proposed heuristic. The base heuristic achieved approximately 86 % of the utility of the greedy approach ($6.78 \times 10^{20}$vs.$7.81 \times 10^{20}$) while including only 23 transactions. The extended version with greedy fill reached up to 120 % of the reference utility ($1.73 \times 10^{21}$), incorporating 268 transactions compared to 212 for the greedy, while maintaining execution times below 2 seconds. These preliminary results demonstrate the feasibility of capturing additional semantic value within time windows compatible with Ethereum block-building intervals, based on isolated experiments with bounded transaction sets.