Abstract
ABSTRACT In the realm of inventory management, the role of substitution in managing growing items is crucial. While several studies have examined growing and substitutable items separately, none have addressed replenishment policies for inventory systems with substitutable growing items. This paper introduces a multi-item inventory management problem for growing items with potential demand substitution. Two cases are defined and mathematically modeled. Due to the nonlinearity of the constrained models, a grid search heuristic algorithm is proposed as the solution methodology. The algorithm’s performance is compared with genetic and simulated annealing algorithms, two state-of-the-art metaheuristics. The models and solution approach are evaluated through numerous numerical examples, demonstrating the grid search heuristic algorithm’s superiority in quality and computational time. Sensitivity analyses are conducted to assess the impact of variations in input parameters on the objective function. Managerial insights are derived from the results, and the paper concludes with directions for future research on both the problem and solution methodology.
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