Bi-objective Optimization Model for Integrated Preventive Maintenance and Flexible Job-shop Scheduling Problem
TL;DR: An integrated model for flexible job-shop scheduling problem with the maintenance activities is developed and two multi objective optimization methods are compared to find the pareto-optimal front in the flexibleJob-shop problem case.
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Abstract: This paper develops an integrated model for flexible job-shop scheduling problem with the maintenance activities. Reliability models are used to perform the maintenance activities. This model involves two objectives: minimization of the maximum completion time for flexible job-shop production part and minimization of system unavailability for the PM (preventive maintenance) part. To aim the objectives, two decisions must be taken at the same time: assigning n jobs on m machines in order to minimize the maximum completion time and finding the appropriate times to perform PM activities to minimize the system unavailability. These objectives are obtained with considering dependent machine setup times for operations and release times for jobs. In advance, the maintenance activity numbers and PM intervals are not fixed. Two multi objective optimization methods are compared to find the pareto-optimal front in the flexible job-shop problem case. Promising the obtained results, a benchmark with a large number of test instances is employed.
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Citations
An efficient two-stage genetic algorithm for a flexible job-shop scheduling problem with sequence dependent attached/detached setup, machine release date and lag-time
TL;DR: The proposed two-stage genetic algorithm (2SGA) with the first stage being different from a typical RGA for FJSP found in the literature is developed, and the sequential version of the proposed algorithm (using a single CPU) outperformed a parallel implementation of the regular genetic algorithm that uses many CPUs.
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References
Bi-objective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible job-shop problem
TL;DR: Four multi-objective optimization methods are compared to find the Pareto-optimal front in the flexible job-shop problem case and results are compared carefully.
169
Bi-objective optimization algorithms for joint production and maintenance scheduling: application to the parallel machine problem
TL;DR: This paper deals with the joint production and maintenance scheduling problem according to a new bi-objective approach that allows the decision maker to find compromise solutions between the production objectives and maintenance ones.
156
An efficient two-stage genetic algorithm for a flexible job-shop scheduling problem with sequence dependent attached/detached setup, machine release date and lag-time
TL;DR: The proposed two-stage genetic algorithm (2SGA) with the first stage being different from a typical RGA for FJSP found in the literature is developed, and the sequential version of the proposed algorithm (using a single CPU) outperformed a parallel implementation of the regular genetic algorithm that uses many CPUs.
68