Decision Support System to Assign Price Rebates of Fresh Horticultural Products Based on Quality Decay

Horticultural products ripeness brings out features like flavor, texture, aroma, skin changes and finally, generates waste due to its spoilage. To avoid or minimize it, many traders as supermarkets, mini-markets and groceries make changes in their fruit’s prices just before expiration date. However, customers’ acceptability changes during the products shelf life, which leads to selling decrease along products quality decay and, consequently, profit decrease. This behavior establishes a challenging scenario to manage stock replenishment and pricing strategies. Many studies present inventory management model for perishable food products but considering only physical quantity deterioration whereas some few authors discuss dynamic pricing, considering quantity and quality deterioration simultaneously. Aiming the optimization of profit in traders, this work introduces a decision support system to assign price rebates of fresh horticultural products based on quality decay. To achieve this goal, two methodologies were followed. The first one consists in using experimental test results for modeling purposes, based on Pontryagin’s maximum principle, using apple, banana and strawberry. The former consists in using questionnaire as sensitivity analysis of quality from customers’ perspective, bringing more reliability and criteria for modeling, since quality could be subjective. The result is a computational decision support system to predict the optimum price for a specific fruit during shelf life. The main objective is to extend the applicability of the computational tool in order to overcome challenges related to limitations of logistics, allowing mini-markets and groceries use this software.