Multi-objective spatio-temporal optimisation for simultaneous planning, design and operation of sustainable and efficient value chains for rice crop

Research output: Contribution to journalArticle

Abstract

The rice value chain, especially in the Philippines, can potentially progress in terms of efficiency and sustainability, as well as create more value by effectively utilising the crop residues of rice production. However, generating multiple products will lead to a complex decision-making process in supply chains, especially in the case of rice crop, which is vital for the Philippines’ food security. Thus, systematic planning techniques are needed to address important decisions along the stages in rice value chains. This study presents a mixed integer linear programming (MILP) model developed for the planning, design and operation of multi-product rice value chains. In order to capture the spatial-dependencies of the problem, such as the candidate locations for rice farms and processing facilities, and location of demands, 81 cells represented the Philippines. The temporal aspect of the model considers a long planning horizon, out to 2050, and the time varying demands for white rice and the crop residues of farming and milling. The model determines design and operating decisions such as where to locate the farms and processing facilities, what products to produce, how to transport resources, among others. Different objectives are considered such as maximisation of the net present value and minimisation of CO2 emissions. The Pareto set generated represents the optimal solutions representing the different trade-offs between economic gain and environmental protection.
Original languageEnglish
Pages (from-to)1453-1458
JournalComputer Aided Chemical Engineering
Volume46
DOIs
Publication statusPublished - 2019

Cite this

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title = "Multi-objective spatio-temporal optimisation for simultaneous planning, design and operation of sustainable and efficient value chains for rice crop",
abstract = "The rice value chain, especially in the Philippines, can potentially progress in terms of efficiency and sustainability, as well as create more value by effectively utilising the crop residues of rice production. However, generating multiple products will lead to a complex decision-making process in supply chains, especially in the case of rice crop, which is vital for the Philippines’ food security. Thus, systematic planning techniques are needed to address important decisions along the stages in rice value chains. This study presents a mixed integer linear programming (MILP) model developed for the planning, design and operation of multi-product rice value chains. In order to capture the spatial-dependencies of the problem, such as the candidate locations for rice farms and processing facilities, and location of demands, 81 cells represented the Philippines. The temporal aspect of the model considers a long planning horizon, out to 2050, and the time varying demands for white rice and the crop residues of farming and milling. The model determines design and operating decisions such as where to locate the farms and processing facilities, what products to produce, how to transport resources, among others. Different objectives are considered such as maximisation of the net present value and minimisation of CO2 emissions. The Pareto set generated represents the optimal solutions representing the different trade-offs between economic gain and environmental protection.",
author = "Stephen Doliente and Sheila Samsatli",
year = "2019",
doi = "10.1016/B978-0-12-818634-3.50243-5",
language = "English",
volume = "46",
pages = "1453--1458",
journal = "Computer Aided Chemical Engineering",
issn = "1570-7946",
publisher = "Elsevier",

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TY - JOUR

T1 - Multi-objective spatio-temporal optimisation for simultaneous planning, design and operation of sustainable and efficient value chains for rice crop

AU - Doliente, Stephen

AU - Samsatli, Sheila

PY - 2019

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N2 - The rice value chain, especially in the Philippines, can potentially progress in terms of efficiency and sustainability, as well as create more value by effectively utilising the crop residues of rice production. However, generating multiple products will lead to a complex decision-making process in supply chains, especially in the case of rice crop, which is vital for the Philippines’ food security. Thus, systematic planning techniques are needed to address important decisions along the stages in rice value chains. This study presents a mixed integer linear programming (MILP) model developed for the planning, design and operation of multi-product rice value chains. In order to capture the spatial-dependencies of the problem, such as the candidate locations for rice farms and processing facilities, and location of demands, 81 cells represented the Philippines. The temporal aspect of the model considers a long planning horizon, out to 2050, and the time varying demands for white rice and the crop residues of farming and milling. The model determines design and operating decisions such as where to locate the farms and processing facilities, what products to produce, how to transport resources, among others. Different objectives are considered such as maximisation of the net present value and minimisation of CO2 emissions. The Pareto set generated represents the optimal solutions representing the different trade-offs between economic gain and environmental protection.

AB - The rice value chain, especially in the Philippines, can potentially progress in terms of efficiency and sustainability, as well as create more value by effectively utilising the crop residues of rice production. However, generating multiple products will lead to a complex decision-making process in supply chains, especially in the case of rice crop, which is vital for the Philippines’ food security. Thus, systematic planning techniques are needed to address important decisions along the stages in rice value chains. This study presents a mixed integer linear programming (MILP) model developed for the planning, design and operation of multi-product rice value chains. In order to capture the spatial-dependencies of the problem, such as the candidate locations for rice farms and processing facilities, and location of demands, 81 cells represented the Philippines. The temporal aspect of the model considers a long planning horizon, out to 2050, and the time varying demands for white rice and the crop residues of farming and milling. The model determines design and operating decisions such as where to locate the farms and processing facilities, what products to produce, how to transport resources, among others. Different objectives are considered such as maximisation of the net present value and minimisation of CO2 emissions. The Pareto set generated represents the optimal solutions representing the different trade-offs between economic gain and environmental protection.

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DO - 10.1016/B978-0-12-818634-3.50243-5

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