Benchmarking NM-SRN v2.0 AGI on the Job-Shop Scheduling Problem (JSSP)

Abstract We present benchmark results for the NM-SRN v2.0 AGI architecture on two canonical instances of the Job-Shop Scheduling Problem (JSSP). Using structured, evolutionary search guided by neural resonance (RE-S), NM-SRN achieved a makespan of 421 on a 10-job, 5-machine instance, and 2621 on a 50-job, 10-machine instance. These results establish a new standard for solvable, traceable solutions to NP-hard scheduling problems using transparent AGI frameworks.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-10
DOI
https://doi.org/10.5281/zenodo.15628240
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
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article

Benchmarking NM-SRN v2.0 AGI on the Job-Shop Scheduling Problem (JSSP)

Zenodo (CERN European Organization for Nuclear Research)
Scheduling and Optimization Algorithms
article

Benchmarking NM-SRN v2.0 AGI on the Job-Shop Scheduling Problem (JSSP)

article en

Abstract

Abstract We present benchmark results for the NM-SRN v2.0 AGI architecture on two canonical instances of the Job-Shop Scheduling Problem (JSSP). Using structured, evolutionary search guided by neural resonance (RE-S), NM-SRN achieved a makespan of 421 on a 10-job, 5-machine instance, and 2621 on a 50-job, 10-machine instance. These results establish a new standard for solvable, traceable solutions to NP-hard scheduling problems using transparent AGI frameworks.

Zenodo (CERN European Organization for Nuclear Research)
Biokine (Israel) (IL), Neural Signals (United States) (US)
Decent work and economic growth
Openalex Percentile: Top 44%
Scheduling and Optimization Algorithms
DOIOpen Access PDFOpenAlex
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Benchmarking NM-SRN v2.0 AGI on the Job-Shop Scheduling Problem (JSSP) · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS