Abstract
This paper investigates a new single machine scheduling problem (SMSP) featuring nonnegative inventory constraints and discretely controllable processing times. Each job contains a single category of item, and the processing of a job would release a predefined number of items into the terminal inventory of the job. A schedule is to properly specify the job and processing time in each operation for minimizing terminal inventories. An exact algorithm and a hybrid metaheuristic are established to solve the problems with different scales. Computational results indicate that the scheduling approaches are effective and efficient in solving the proposed SMSP.
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