Multi-objective optimization for integrated production scheduling and maintenance planning
Submitted: 2025-01-09
|Accepted: 2026-01-25
|Published: 2026-01-31
Copyright (c) 2026 Rifqi Fauzi, Nur Aini Masruroh
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Keywords:
Job Shop, Maintenance, Scheduling, Integration, NSGA-II, MOALNS
Supporting agencies:
Universitas Negeri Malang
Abstract:
The search for integrated solutions in the machining industry, particularly in job shop production scheduling and maintenance planning, is crucial. This development aims to simultaneously inform production scheduling decisions and maintenance planning, thereby minimizing makespan and operational costs. The limited time for decision-making on an industrial scale presents a challenge in providing fast and optimal decisions. Therefore, optimization is carried out using an approximation approach: NSGA-II and MOALNS. A multi-objective optimization model has been successfully developed and can provide optimal results for the integrated production and maintenance scheduling. The mathematical model demonstrated robustness in various solved cases. NSGA-II reduced operational costs by up to 28% but increased makespan by 4%. In comparison, MOALNS reduced the makespan by up to 4% but only reduced operational costs by up to 16%. Finally, NSGA II consistently provides better performance results than MOALNS. With significant reductions in operational costs, the industry can save significantly on total operational costs, such as machine maintenance, labor costs, and maintaining output quality, from existing operations and can continue to serve customers more sustainably. NSGA-II is superior in covering the objective function space, achieving solution quality close to the Pareto front, and maintaining a consistent distribution of solutions.
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