Degradation-Aware Single-Machine Scheduling with Price-Driven Thresholding and Waiting Triggers

Zhaoyi Zhang; Chumpol Yuangyai; Chen-Yang Cheng; Ranon Jientrakul; Nagoor Basha Shaik

doi:10.55003/ETH.430307

Authors

Zhaoyi Zhang School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand
Chumpol Yuangyai School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand
Chen-Yang Cheng National Taipei University of Technology, Republic of China
Ranon Jientrakul School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand
Nagoor Basha Shaik School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand

DOI:

https://doi.org/10.55003/ETH.430307

Keywords:

Time-of-use Electricity Pricing, Degradation-aware Scheduling, Reliability Threshold Policy, Preventive Maintenance, Weighted Tardiness

Abstract

This paper studies a degradation-aware non-preemptive single-machine scheduling problem under time-of-use (TOU) and flat (FLAT) electricity tariffs. The objective is to minimize total cost, including processing energy, optional waiting energy, preventive maintenance (PM), and weighted tardiness. The model links reliability degradation to processing power through an interpretable reliability-power mapping and uses an MTBF-calibrated exponential reliability function with PM restoration. We propose a price-driven adaptive reliability threshold rₜₕ(t), bounded by rₘᵢₙ and rₘₐₓ, and a conservative waiting trigger that is activated only when due-date slack is sufficient and the expected price decrease is meaningful. Under FLAT pricing, the adaptive term vanishes and the policy degenerates to the static baseline, providing a direct consistency check. For computation, PM and waiting decisions are generated by policy rules, whereas metaheuristics optimize the job permutation. A permutation-based Tabu Search (TS) is compared with GA, SA, ACO, and DE-RK on OR-Library WT40/WT50/WT100 instances. The results show rational TOU responsiveness, small-instance optimality references, and non-additive interactions between threshold adaptiveness and waiting under strong due-date pressure. The framework provides auditable decision logic for scheduling and maintenance under time-varying electricity prices.

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