A STOCHASTIC OPTIMIZATION MODEL FOR A JOINT PRICING AND RESOURCE ALLOCATION PROBLEM

In a competitive and volatile market, the price is needed to make in consideration of the uncertain demands of the customers and the limited capacities of enterprises. This requires the coordination decisions on pricing, delivery and resource allocation to increase profit and guarantee service quality for firms. The joint decision on pricing and resource allocation with demand and processing time uncertainty is becoming an issue for a profit-maximizing firm that produces various products. We propose a two-stage model based on stochastic programming to address this joint problem. aiming to maximize profit of products. We present a scenario-simulation approach to describe the stochastic variables; then the deterministic two-stage mixed integer linear programming model is formulated depending on those scenarios. We develop an algorithm by ant colony algorithm to obtain the near-optimal solutions of the models above. The numerical experiments were conducted to validate the proposed models. The results show that the stochastic approach outperfonns the deterministic model in the different problem scales and yield the better values of compared metrics. The outcomes also imply that this joint pricing model can provide managerial inspiration for enterprises in the customization environment.