Optimization of Inventory for Optimal Replenishment Policies and Lead-Time with Time Varying Demand
Considering a single period inventory management problem used in the distribution channel to represent consumer demand for marketing/sales of a product, attempt is made to develop a deterministic inventory model with time-varying increasing demand that may be used to reflect sales in different phases of a product life cycle in the competitive market. We propose inventory model assuming replenishment cost is to be linearly dependent on lot size and purchasing cost per unit item is dependent on lead time. Lead time is taken as decision variable. Shortages are allowed to backlog and to lose partly. Our objective is to cumulatively evaluate optimal replenishment lot-size, order time and lead-time for maximization of total profit. Considering the complexities of the proposed model, we propose a heuristic solution approach by developing an ERCM Genetic Algorithm based on ranking section, elitism, whole arithmetic crossover and non-uniform mutation dependent on the age of the population. This heuristics are easy to compute and practical to implement, and perform well in numerical trials.