Incorporating Return on Inventory Investment into Joint Lot-Sizing and Price Discriminating Decisions: A Fuzzy Chance Constraint Programming Model

Abstract

Coordination of market decisions with other aspects of operations management such as production and inventory decisions has long been a meticulous research issue in supply chain management. Generally, changes to the original lot-sizing policy stimulated by market prices may impose remarkable deviation revenue throughout the supply and demand chain system. This paper examines how to set the channel prices and the lot-sizing quantities so that the potential maximal return on investment is gained under a differential pricing scenario involving a number of possibilistic constraints to deal with market-segmented price setting, marketing and lot-sizing decisions, concurrently. The model aims to maximize return on inventory investment (ROII). To solve the model, a fuzzy solution approach based on the novel credibility measure is developed. An efficient and tuned search procedure using particle swarm optimization is tailored to reach the solutions of the resultant non-linear crisp model. An illustrative example is also studied to demonstrate the practicability of the proposed mathematical model and its solution approach.