A Simulation-optimization Approach for Replenishment Planning and Shelf Space Allocation in Retail Industry under Zone- and Stock-dependent Demand

Document Type: Research Paper

Authors

Abstract

A
simulation-optimization approach is proposed for replenishment planning and
shelf space allocation. The customers’ demand is divided into fixed and
variable demand. Each customer follows a given path while shopping in the
store. By dividing the store space into several zones and calculating the
related substantial and random utilities, an analytical equation is proposed
for the probability of zone visits. Due to the complexity of the proposed
equation, a simulation method is used to evaluate the customers’ movements and
predict the variable demand. A profit-based integer-programming model is then
formulated for the case problem that needs the output demand of the
simulation phase. However, the optimal values of some decision variables should
be available through simulation. Therefore, a simulation-optimization algorithm
is iteratively run since a pre-determined small deviation from the expected
profit goal is achieved. Finally, the numerical results are reported for a
small-sized problem.

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