ORCID Identifier(s)

0000-0002-6948-538X

Graduation Semester and Year

2020

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Jamie Rogers

Second Advisor

Caroline Krejci

Third Advisor

Jaime Cantu

Abstract

Access to high quality and safe food is vital for sustainable development in societies. Perishable foods lose a major portion of their quality after harvesting until the consumption point due to poor storage and distribution conditions. Thus, improvements in food supply chain operations are very critical in the sustainable development of society and the industry. The first part of this dissertation seeks to find a cost-effective and reliable tool to monitor the quality loss and implementation of the least shelf life first-out inventory management policy in food banks. Application of the Gompertz model and Arrhenius equation based on time-temperature data collected from donated foods provides an accurate and reliable estimation for the shelf life through the inbound operations. As a result of applying this methodology, perishable products which have the least shelf life are selected first to distribute among the people in need. Furthermore, as the role of food distribution is highlighted in the literature, the next two sections of this dissertation discuss how to increase efficiency and improve sustainability in the distribution of perishable food products. In chapter 3, temperature abuses and long delivery routes are identified as the main reasons that foods lose a considerable portion of their quality during distribution. Energy equations are applied to predict temperature increases when the container door is open to unload part of the cargo in the location of a customer. These temperature estimates are used as the input of the Gompertz model and the Arrhenius equation to predict the remaining shelf life of foods when they are delivered at their destination. Loss in the shelf life of the delivered products can be transformed into the revenue loss and discarding cost which can be integrated with other distribution costs in the objective function of the perishable food distribution model. Simulated Annealing algorithm is developed to solve the proposed mathematical model. The results of comparing the proposed quality dependent perishable food distribution model with the conventional food distribution model show that the total distribution costs in the proposed model are lower than the conventional model, and this gap goes up as the size of the problem increases. In chapter 4, the main influential elements in the sustainability of perishable food distribution networks are identified as distribution costs, CO2 emission which comes from the diesel engine of the refrigerated vehicle, and freshness of foods. A novel multi-objective mathematical model is developed to consider each of these impactful factors as an objective of the model. The freshness of the products are measured by integration of the temperature and shelf life prediction models, the CO2 emission is calculated based on the energy consumed to transport and refrigerate the perishable foods, and the distribution costs are the combination of the fixed dispatching costs and variable costs of transporting products between two locations. Non-dominated sorting genetic algorithm II is developed to solve the multi-objective model. The performance of the solution algorithm is verified by comparing it with a weighted Simulated Annealing algorithm. The analysis over the results illustrates that the sustainability goals are conflicting in nature, and optimizing any of these goals leads to the optimality gap in other objectives. The results show that the sustainability goals of perishable food distribution are sensible to the shelf life of the foods, and foods with lower shelf life imply higher distribution costs, CO2 emission, and lower freshness. Also, the results show that when temperature sets for higher degrees inside the container of refrigerated vehicles, although CO2 emission is lower the freshness of perishable foods is getting worse.

Keywords

Sustainable distribution, Food perishability, Multi-objective optimization, Temperature prediction, Shelf life, Food waste

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

30679-2.zip (1529 kB)

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