a simulation-optimization approach for replenishment planning and shelf space allocation in retail industry under zone- and stock-dependent demand

asimulation-optimization approach is proposed for replenishment planning andshelf space allocation. the customers’ demand is divided into fixed andvariable demand. each customer follows a given path while shopping in thestore. by dividing the store space into several zones and calculating therelated substantial and random utilities, an analytical equation is proposedfor the probability of zone visits. due to the complexity of the proposedequation, a simulation method is used to evaluate the customers’ movements andpredict the variable demand. a profit-based integer-programming model is thenformulated for the case problem that needs the output demand of thesimulation phase. however, the optimal values of some decision variables shouldbe available through simulation. therefore, a simulation-optimization algorithmis iteratively run since a pre-determined small deviation from the expectedprofit goal is achieved. finally, the numerical results are reported for asmall-sized problem.