Abstract
This paper proposes an approach to optimize Kazakhstan’s track maintenance machine fleet by incorporating forecasted railway track condition. The study analyzes freight turnover and infrastructure wear trends for 2014-2024 under growing transit/export loads: freight turnover increased from 214 to 327.9 billion t-km, while infrastructure wear rose from 38% to 57%; according to JSC «KTZ», in January 2025 mainline loading grew by 7.3% to 21.7 million tons, and export transportation increased by 13.4%. Maintenance demand is justified using regulatory track-condition thresholds, speed decisions under defects, and repair assignment criteria. The scientific novelty lies in a decision-making algorithm that explicitly links forecasted track condition to regulatory limits and selects the optimal «retain – modernize – renew» scenario using profit maximization (Π = D – C) as the objective. The practical outcome is an applied methodology for defining the rational fleet composition (machine types/ quantity) for planned maintenance volumes in a system operating approximately 543 units of track machinery; it is intended to reduce equipment downtime, improve resource allocation, and enhance maintenance program deliverability under increasing operational loads