Managing Real-time Demand Fluctuation
In this research, we (Paul, Sarker and Essam) have considered a supplier-retailer system, which operates under an agreed coordinated policy, with an imperfect production process and a possibility of having demand fluctuation. In this research, a dynamic planning process is proposed to deal with short-term demand fluctuations. Firstly, a mathematical model has been developed for a single fluctuation that generates a revised plan, after the occurrence of the fluctuation event, either for increasing or decreasing demand rate. We propose a new and efficient heuristic to solve the developed model. Secondly, multiple fluctuations have been considered, for which a new occurrence may or may not affect the revised plan of earlier occurrences and we extend the heuristic that is capable to deal with multiple demand fluctuations on a real time basis. We have generated a good number of random test problem and also solved the model using a genetic algorithm, in order to compare the solutions with our heuristic. The comparison confirmed the consistent performance of our developed heuristic, and also its lower computational time. Numerical examples and sensitivity analysis have been presented to explain the usefulness of the developed model.