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Advisor(s)
Abstract(s)
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 groceriesmake 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 formodeling purposes, based on Pontryagin’smaximum 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.
Description
Keywords
Food waste Mathematical modelling Perishable products Decision support system Price rebates Quality decay
Citation
Publisher
Springer