Optimal Transport Planning for the Supply to a Fruit Logistic Centre

Nadal-Roig, Esteve; Plà-Aragonés, Lluís M.

doi:10.1007/978-1-4939-2483-7_7

Cited by 21 publications

(14 citation statements)

References 12 publications

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“…There are two essential types of fruit used for case studies: perennial crops such as apples [18][19][20][21], oranges [6,12], pome fruit [10], pears [16,22,23], cherries [24] and grapes [4,25,26] or annual crops such as pineapple [27], strawberries [28], melon [29], and tomato [13,30,31]. Dragon fruit is a tropical fast-growing perennial crop, other examples being asparagus [32], Persian lime [33], Thai soursop, Taiwan pear-shaped guava, etc.…”

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confidence: 99%

Optimization Model for Fresh Fruit Supply Chains: Case-Study of Dragon Fruit in Vietnam

et al. 2019

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We present an optimization model for dragon fruit plantations in Vietnam. The timing of cultivating and harvesting decisions are taken into account as the dragon fruit plant has an approximately ten-year life cycle with maximum average yield in the fourth year. Another consideration also included is the prevalence of forward-buying contracts with locked-in prices. The dragon fruit supply chain faces several difficulties as yield, price, and demand are highly sensitive to weather conditions and global uncertainty factors. The risk factors in the dragon fruit supply chain also depend on species-for example, the red varieties, while more profitable than the white varieties, also have higher export risk because they are subject to global prices and adverse geopolitical conditions.

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Optimization Model for Fresh Fruit Supply Chains: Case-Study of Dragon Fruit in Vietnam

et al. 2019

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“…Verdouw et al (2010) elaborated a basic model for designing fresh and processed fruit SCs. A transport planning model for the FSCs, in which several storage centers provide a fruit logistics center on demand during the off season, was developed by Nadal-Roig and Pla-Aragones (2015).…”

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confidence: 99%

A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network

Jabarzadeh

Yamchi

Kumar

et al. 2020

MEQ

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PurposeThis paper aims to present a closed-loop supply chain (CLSC) optimization problem for a perishable agricultural product to achieve three pillars of sustainability, including minimizing total network costs and carbon dioxide emissions from different network activities and maximizing responsiveness to demands simultaneously.Design/methodology/approachThe research problem is formulated as a multi-objective mixed-integer linear programming model, and classical approaches, including the LP-Metric and weighted Tchebycheff method, have been applied to solve the optimization model. A set of test problems has been proposed to validate the model, and the results are presented.FindingsComputational time to find Pareto optimal solutions by using the weighted Tchebycheff method was twice as much as that of the LP-Metric method. Also, the result of the study is a mathematical model that can be applied to other products that are close to the fruit, such as vegetables.Research limitations/implicationsThe present study is limited to fruits supply chains and the inventory is considered at the distribution centers only. The study also considers only one type of transport.Practical implicationsThe paper can assist supply chain managers to define strategies to achieve a sustainable CLSC network configuration for the fruits.Originality/valueThis study is one of the early studies to consider environmental indicators in fruits supply chain design along with two other indicators of sustainability, namely, economic and social indicators. Therefore, this can help supply chain managers to achieve sustainability by optimizing location decisions, inventory quantities and flow between facilities.

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“…The proposed models were solved through metaheuristics, using modifications of ant colony optimization. On the other hand, the work of Nadal‐Roig and Plà‐Aragonés (2015) presents a mixed‐integer programming (MIP) problem to cooperate with decision making within a fruit distribution center (FLC). Thus, planning of the transport of resources within this company is generated, establishing an objective function that seeks to minimize daily transport costs, adding to this problem restrictions such as the capacity of each truck and the total amount of transported fruit.…”

Section: Literature Reviewmentioning

confidence: 99%

Linear programming based decision support system for grapes transport planning in CAPEL

Monardes-Concha

Serrano‐Julio

Hoffmann³

2020

Int Trans Operational Res

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This research is about developing a decision support system (DSS) for the distribution of grapes and grape must in a Chilean cooperative, Cooperativa Agrícola Pisquera Elqui Limitada (CAPEL). CAPEL is dedicated to producing and distributing several beverages such as sparkling wines, beers, energy drinks, rum, and pisco. This work aims to support the grinding‐related transport stage through a linear programming based DSS, in order to find the optimal use of the transport demand in a network based on source and destination plants during the harvest season. To achieve this aim, an operational research (OR) model that feeds the DSS is developed, whose objective function seeks to minimize the total transport cost. The decision variables define the grape cargo to be transported from a source plant to a destination plant. The OR model uses constraints such as transportation demand, grinding capacity, maximum storage, and available grape in plants. The model succeeded in reducing the total transport costs by 14% for the 2017 season of the pisco‐making process, meaning approximately savings of 59 million Chilean pesos.

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Optimal Transport Planning for the Supply to a Fruit Logistic Centre

Cited by 21 publications

References 12 publications

Optimization Model for Fresh Fruit Supply Chains: Case-Study of Dragon Fruit in Vietnam

Optimization Model for Fresh Fruit Supply Chains: Case-Study of Dragon Fruit in Vietnam

A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network

Linear programming based decision support system for grapes transport planning in CAPEL

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