Abstract
This paper studies a challenging case of joint lot sizing and scheduling in a manufacturing plant for animal feed compounds. A key characteristic of this industry is that certain products can perform a production line “cleaning” function if a sufficiently large lot is produced between two products that would otherwise require a cleaning setup. Thus the sequence-dependent setup times do not always obey the triangular inequality. A mixed integer programming model is applied and tested on multiple sets of real data from different seasons. The model takes too long to solve exactly and so alternative formulations and methods are developed to solve the model more quickly, based on two variants of the Relax and Fix heuristic. Test results demonstrate that the formulations are computationally effective and able to take economic advantage of the intermediate cleaning products. The model schedule substantially improves on that practiced at the plant and can be useful for similar companies in the animal-feed industry.
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