Neighbourhood Based Robustness Applied to Tardiness and Total Flowtime Job Shops
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Heuristic stability: A permutation disarray measure
Computers and Operations Research
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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Applied Soft Computing
Expert Systems with Applications: An International Journal
A robust scheduling method based on a multi-objective immune algorithm
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Economic design of variable sampling intervals T2 control charts using genetic algorithms
Expert Systems with Applications: An International Journal
Optimization of phase angle measurement unit placement
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Robust model for job shop scheduling with uncertain processing times
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Analysis of robustness in proactive scheduling: A graphical approach
Computers and Industrial Engineering
Integrating rush orders into existent schedules for a complex job shop problem
Applied Intelligence
Expert Systems with Applications: An International Journal
Business process scheduling with resource availability constraints
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Rescheduling of flexible job shops under machine breakdowns
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Computers and Industrial Engineering
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The problem of finding robust or flexible solutions for scheduling problems is of utmost importance for real-world applications as they operate in dynamic environments. In such environments, it is often necessary to reschedule an existing plan due to failures (e.g., machine breakdowns, sickness of employees, deliveries getting delayed, etc.). Thus, a robust or flexible solution may be more valuable than an optimal solution that does not allow easy modifications. This paper considers the issue of robust and flexible solutions for job shop scheduling problems. A robustness measure is defined and its properties are investigated. Through experiments, it is shown that using a genetic algorithm it is possible to find robust and flexible schedules with a low makespan. These schedules are demonstrated to perform significantly better in rescheduling after a breakdown than ordinary schedules. The rescheduling performance of the schedules generated by minimizing the robustness measure is compared with the performance of another robust scheduling method taken from literature, and found to outperform this method in many cases.