An analysis of crop-livestock systems using strongly connected components and multi-objective optimization

Crop-livestock farming has been a method introduced in ancient civilizations where crops of different varieties are incorporated with one or more varieties of animal species. It provided opportunities for biodiversity in both plant and animal life in order to promote nutrient recycling, regulate pes...

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Bibliographic Details
Main Authors: Guarisma, Jose Paolo Olano, Hilario, Ma. Clarisa Ruizo
Format: text
Language:English
Published: Animo Repository 2023
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etdb_math/23
https://animorepository.dlsu.edu.ph/context/etdb_math/article/1026/viewcontent/2023_Guarisma_Hilario_An_Analysis_of_Crop_Livestock_Systems_Full_text.pdf
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Institution: De La Salle University
Language: English
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Summary:Crop-livestock farming has been a method introduced in ancient civilizations where crops of different varieties are incorporated with one or more varieties of animal species. It provided opportunities for biodiversity in both plant and animal life in order to promote nutrient recycling, regulate pest infestations and optimize the available land area within their community. With the agricultural sector facing numerous challenges over the years with the rise of pest infestations in relation to targeted pests having an increased resistance to pesticides as well as a decline in land quality and quantity with the rise of industrialization, there has been numerous frameworks and research that propose revisiting the benefits from past methods for a more sustainable form of farming. In this paper, we aim to identify mutually beneficial crop-livestock systems with the use of Kosaraju’s algorithm in finding strongly connected components as a way to introduce systems that provide pest regulation and increase soil fertility. A multi-objective optimization such as epsilon-constraint method will be utilized to find the optimal solution to maximize pest control within the system and to maximize soil fertility.