Tesis doctorals> Departament d'Enginyeria Química

Development of advanced mathematical programming methods for supply chain management

  • Identification data

    Identifier: TDX:1171
    Authors:
    Kostin, Andrey
    Abstract:
    The aim of this thesis is to provide a decision-support tool for the strategic planning of supply chains (SCs). The task consists of determining the number, location and capacities of all SC facilities, their expansion policy, the transportation links that need to be established, and the production rates and flows of all materials involved in the network. The problem is formulated as a mixed-integer linear programming (MILP) model, which is solved using several mathematical programming tools. First, a decomposition strategy was developed to expedite the solving procedure. Second, the approximation algorithm was utilized to solve the stochastic version of the MILP. Finally, the multi-objective model was developed to incorporate the trade-off between economical and ecological issues. All formulations were applied to a real case based on the Argentinean sugarcane industry. The tools presented are intended to help policy-makers in the strategic planning of infrastructures for chemicals production.
  • Others:

    Date: 2013-03-18
    Departament/Institute: Departament d'Enginyeria Química Universitat Rovira i Virgili.
    Language: eng
    Identifier: http://hdl.handle.net/10803/108957
    Source: TDX (Tesis Doctorals en Xarxa)
    Author: Kostin, Andrey
    Director: Jiménez Esteller, Laureano Guillén Gosálbez, Gonzalo
    Format: application/pdf 141 p.
    Publisher: Universitat Rovira i Virgili
    Keywords: Multiobjective optimization Life cycle assessment Supply chain management
    Title: Development of advanced mathematical programming methods for supply chain management
    Subject: 66 - Enginyeria, tecnologia i indústria química. Metal·lúrgia
  • Keywords:

    66 - Enginyeria, tecnologia i indústria química. Metal·lúrgia
  • Documents:

  • Cerca a google

    Search to google scholar