Agricultural Cooperative

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Nacima Labadie - One of the best experts on this subject based on the ideXlab platform.

  • Predictive modelling with panel data and multivariate adaptive regression splines: case of farmers crop delivery for a harvest season ahead
    Stochastic Environmental Research and Risk Assessment, 2016
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper investigates a harvest-season level unbalanced panel data (PD) of farmers crop delivery for monitoring the gathering activity and for aiding to support reception and storage decisions making of an Agricultural Cooperative. To achieve these purposes, the fitting and the prediction of the daily farmers crop delivery quantities were realised based-on the total expected quantity of the whole harvest season, the daily volume of precipitation and the amount of sunshine. In order to capture and extrapolate data patterns, both the PD regression and the multivariate adaptive regression approaches were implemented and tested for a real life Agricultural Cooperative case study. The obtained results exhibit an accurate predictive modelling of the farmers crop delivery behaviour for harvest seasons ahead.

  • An application of the discrete event simulation for efficient crop production supply chain redesign
    2014
    Co-Authors: Valeria Borodin, Nacima Labadie, Faicel Hnaien, Jean Bourtembourg
    Abstract:

    Given the new challenges confronting Agricultural sector, innovative (alternative) production policies need to be devise and design at the farm level. Due to its involved high cost, re-configuring experiments are not easy and circumspect to conduct at this level, a beforehand modelling is required for a scrupulous evaluation of multiple impacts of any eventual alternative re-conguration. In this sense, focused on crop production supply chain encountered at a typical French Agricultural Cooperative, this study investigates an alternative storage policy based-on the pooling of growers and Cooperative resources and efforts during the harvest season. By raising awarenesses on deterministic and stochastic components, a discrete event simulation modellings of the both current and alternative crop supply chain are presented and confronted for an efficient crop streaming from growing fields to long-term storage facilities.

  • an interval programming approach for an operational transportation planning problem
    International Conference Information Processing, 2014
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper deals with an interval programming approach for an operational transportation problem, arising in a typical Agricultural Cooperative during the crop harvest time. More specifically, an interval programming model with uncertain coefficients occurred in the right-hand side and the objective function is developed for a single-period multi-trip planning of a heterogeneous fleet of vehicles, while satisfying the stochastic seed storage requests, represented as interval numbers. The proposed single-period interval programming model is conceived and implemented for a real life Agricultural Cooperative case study.

  • A quality risk management problem: case of annual crop harvest scheduling
    International Journal of Production Research, 2013
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper presents a stochastic optimisation model for the annual harvest scheduling problem of the farmers’ entire cereal crop production at optimum maturity. Gathering the harvest represents an important stage for both Agricultural Cooperatives and individual farmers due to its high cost and considerable impact on seed quality and yield. The meteorological conditions represent the deciding factor that affects the harvest scheduling and progress. Using chance-constrained programming, a mixed-integer probabilistically constrained model is proposed, with a view to minimising the risk of crop quality degradation under climate uncertainty with a safe confidence level. The chance-constrained optimisation problem is tackled and solved via an equivalent linear mixed-integer reformulation jointly with scenario-based approaches. Moreover, a new concept of -scenario pertinence is introduced in order to defy efficiently the probabilistically constrained problem complexity and time limitations. From the practical standpoint, this study is aimed at helping an Agricultural Cooperative in decision-making on crop quality risk management and harvest scheduling over a medium time horizon (10–15 time periods).

  • A discrete event simulation model for harvest operations under stochastic conditions
    2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING SENSING AND CONTROL (ICNSC), 2013
    Co-Authors: Valeria Borodin, Nacima Labadie, Faicel Hnaien, Jean Bourtembourg
    Abstract:

    This study presents an application of stochastic discrete-event simulation modelling for harvesting, transportation and storage activities of one grain and oilseed Agricultural Cooperative. Gathering the harvest represents an important stage for both Agricultural Cooperatives and individual farmers, that requires an efficient management in order to ensure a high production quality and yield. For the purpose to take into account the intricacy and the dynamic behaviour of the studied system, the model proposed here, considers various inherent heterogeneous parameters, such as: daily meteorological uncertainty, loss queuing networks, farmers contractual delivery policies, etc. This paper applies discrete and stochastic simulation techniques in order to analyse and evaluate the performance of the Cooperative supply chain system. Moreover, it enables to investigate alternative configurations and strategies of its operations for an eventual supply chain redesign.

Alexander Borst - One of the best experts on this subject based on the ideXlab platform.

Jiang Chen - One of the best experts on this subject based on the ideXlab platform.

Valeria Borodin - One of the best experts on this subject based on the ideXlab platform.

  • Predictive modelling with panel data and multivariate adaptive regression splines: case of farmers crop delivery for a harvest season ahead
    Stochastic Environmental Research and Risk Assessment, 2016
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper investigates a harvest-season level unbalanced panel data (PD) of farmers crop delivery for monitoring the gathering activity and for aiding to support reception and storage decisions making of an Agricultural Cooperative. To achieve these purposes, the fitting and the prediction of the daily farmers crop delivery quantities were realised based-on the total expected quantity of the whole harvest season, the daily volume of precipitation and the amount of sunshine. In order to capture and extrapolate data patterns, both the PD regression and the multivariate adaptive regression approaches were implemented and tested for a real life Agricultural Cooperative case study. The obtained results exhibit an accurate predictive modelling of the farmers crop delivery behaviour for harvest seasons ahead.

  • An application of the discrete event simulation for efficient crop production supply chain redesign
    2014
    Co-Authors: Valeria Borodin, Nacima Labadie, Faicel Hnaien, Jean Bourtembourg
    Abstract:

    Given the new challenges confronting Agricultural sector, innovative (alternative) production policies need to be devise and design at the farm level. Due to its involved high cost, re-configuring experiments are not easy and circumspect to conduct at this level, a beforehand modelling is required for a scrupulous evaluation of multiple impacts of any eventual alternative re-conguration. In this sense, focused on crop production supply chain encountered at a typical French Agricultural Cooperative, this study investigates an alternative storage policy based-on the pooling of growers and Cooperative resources and efforts during the harvest season. By raising awarenesses on deterministic and stochastic components, a discrete event simulation modellings of the both current and alternative crop supply chain are presented and confronted for an efficient crop streaming from growing fields to long-term storage facilities.

  • an interval programming approach for an operational transportation planning problem
    International Conference Information Processing, 2014
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper deals with an interval programming approach for an operational transportation problem, arising in a typical Agricultural Cooperative during the crop harvest time. More specifically, an interval programming model with uncertain coefficients occurred in the right-hand side and the objective function is developed for a single-period multi-trip planning of a heterogeneous fleet of vehicles, while satisfying the stochastic seed storage requests, represented as interval numbers. The proposed single-period interval programming model is conceived and implemented for a real life Agricultural Cooperative case study.

  • A quality risk management problem: case of annual crop harvest scheduling
    International Journal of Production Research, 2013
    Co-Authors: Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie
    Abstract:

    This paper presents a stochastic optimisation model for the annual harvest scheduling problem of the farmers’ entire cereal crop production at optimum maturity. Gathering the harvest represents an important stage for both Agricultural Cooperatives and individual farmers due to its high cost and considerable impact on seed quality and yield. The meteorological conditions represent the deciding factor that affects the harvest scheduling and progress. Using chance-constrained programming, a mixed-integer probabilistically constrained model is proposed, with a view to minimising the risk of crop quality degradation under climate uncertainty with a safe confidence level. The chance-constrained optimisation problem is tackled and solved via an equivalent linear mixed-integer reformulation jointly with scenario-based approaches. Moreover, a new concept of -scenario pertinence is introduced in order to defy efficiently the probabilistically constrained problem complexity and time limitations. From the practical standpoint, this study is aimed at helping an Agricultural Cooperative in decision-making on crop quality risk management and harvest scheduling over a medium time horizon (10–15 time periods).

  • A discrete event simulation model for harvest operations under stochastic conditions
    2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING SENSING AND CONTROL (ICNSC), 2013
    Co-Authors: Valeria Borodin, Nacima Labadie, Faicel Hnaien, Jean Bourtembourg
    Abstract:

    This study presents an application of stochastic discrete-event simulation modelling for harvesting, transportation and storage activities of one grain and oilseed Agricultural Cooperative. Gathering the harvest represents an important stage for both Agricultural Cooperatives and individual farmers, that requires an efficient management in order to ensure a high production quality and yield. For the purpose to take into account the intricacy and the dynamic behaviour of the studied system, the model proposed here, considers various inherent heterogeneous parameters, such as: daily meteorological uncertainty, loss queuing networks, farmers contractual delivery policies, etc. This paper applies discrete and stochastic simulation techniques in order to analyse and evaluate the performance of the Cooperative supply chain system. Moreover, it enables to investigate alternative configurations and strategies of its operations for an eventual supply chain redesign.

James Barham - One of the best experts on this subject based on the ideXlab platform.