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Data-Driven Planning for Food and Forest Supply Chains Under Disruptions.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Data-Driven Planning for Food and Forest Supply Chains Under Disruptions./
Author:	Elimbi Moudio, Marie Pelagie.
Description:	1 online resource (122 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
Subject:	Industrial engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798380877855

Data-Driven Planning for Food and Forest Supply Chains Under Disruptions.
Elimbi Moudio, Marie Pelagie.

Data-Driven Planning for Food and Forest Supply Chains Under Disruptions. - 1 online resource (122 pages)

Source: Dissertations Abstracts International, Volume: 85-06, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2023.

Includes bibliographical references

Global disruptions such as the Covid-19 pandemic emphasize the fragile nature of connected supply chains and the impact of these interruptions on our daily lives. The alarming growth in the type and number of disruptions complicates planning efforts and will lead to increased losses in the absence of efficient systems that reduce complexity for policy makers. We investigate food and forestry supply chains, key systems for human survival. In the context of food and agricultural supply chains, disruptions have not only caused bottlenecks in different stages of food supply chains but also exposed the need for holistic solutions to food supply and allocation. To tackle this challenge, we model a two-stage stochastic resource allocation problem with non-linear connectivity costs to capture trade dynamics between countries. We compare model recommendations to historical trade flow data including coffee trade between countries, unveiling the value of centralized planning under potential disruption scenarios against the current practices. In another chapter, we design and incrementally update a data-driven network risk measure that focuses on including the downstream impact of nodes. starting with a hand crafted intuitive risk measure then the Downstream Protection Value (DPV) and finally proposing the Downstream Supply Risk Measure (DSRM). The consistency in results between DPV and DSRM measures is investigated and their limitations are discussed. Additionally, the existence of a large variety of food products that are exchanged within and across countries renders the creation of separate policies for each product impractical. To aid this problem, we develop a framework to systematically group different food product supply chains by identifying their structure using world bank trade data between countries for $53$ different products over a period of $25$ years. Decision makers can thus create policies for food networks at the group level instead of individual policies for the large variety of food and agricultural products. In the context of Forestry systems, we extend an existing fuel treatment allocation model to include socio-environmental costs to the objective function. We investigate how to develop efficient action to mitigate future fires (fuel treatment plans) so as to mitigate risk in Forestry supply chains. In the long run, developing an understanding of the impacts of risk and how they can be mitigated will be essential in resolving their lasting and usually devastating impacts to the world ecosystem.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380877855Subjects--Topical Terms:

679492
Industrial engineering.
Subjects--Index Terms:

Decision-makingIndex Terms--Genre/Form:

554714
Electronic books.

Data-Driven Planning for Food and Forest Supply Chains Under Disruptions.
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