Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine
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This paper deals with serial-batching scheduling problems with the effects of deterioration and learning, where time-dependent setup time is also considered. In the proposed scheduling models, all jobs are first partitioned into serial batches, and then all batches are processed on a single serial-batching machine. The actual job processing time is a function of its starting time and position. In addition, a setup time is required when a new batch is processed, and the setup time of the batches is time-dependent, i.e., it is a linear function of its starting time. Structural properties are derived for the problems of minimizing the makespan, the number of tardy jobs, and the maximum earliness. Then, three optimization algorithms are developed to solve them, respectively.
KeywordsScheduling Serial-batching Deteriorating jobs Learning effect Single-machine
This work is supported by the National Natural Science Foundation of China (Nos. 71231004, 71171071, 71131002, 71201042), and the Fundamental Research Funds for the Central Universities (Nos. JZ2015HGBZ0116, JZ2015HGBZ0117, JZ2015HGQC0187). Panos M. Pardalos is partially supported by the project of “Distinguished International Professor by the Chinese Ministry of Education” (MS2014HFGY026).
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