Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

Coupling Soft Computing, Simulation and Optimization in Supply Chain Applications: Review and Taxonomy

  • Identification data

    Identifier: imarina:9366549
    Authors:
    El Raoui, HOudani, MAlaoui, AE
    Abstract:
    Supply chain networks are typical examples of complex systems. Thereby, making decisions in such systems remains a very hard issue. To assist decision makers in formulating the appropriate strategies, robust tools are needed. Pure optimization models are not appropriate for several reasons. First, an optimization model cannot capture the dynamic behavior of a complex system. Furthermore, most common practical problems are very constrained to be modeled as simple tractable models. To fill in the gap, hybrid optimization/simulation techniques have been applied to improve the decision-making process. In this paper we explore the near-full spectrum of optimization methods and simulation techniques. A review and taxonomy were performed to give an overview of the broad field of optimization/simulation approaches applied to solve supply chain problems. Since the possibilities of coupling them are numerous, we launch a discussion and analysis that aims at determining the appropriate framework for the studied problem depending on its characteristics. Our study may serve as a guide for researchers and practitioners to select the suitable technique to solve a problem and/or to identify the promising issues to be further explored.
  • Others:

    Author, as appears in the article.: El Raoui, H; Oudani, M; Alaoui, AE
    Department: Enginyeria Electrònica, Elèctrica i Automàtica
    URV's Author/s: El Aroudi Chaoui, Abdelali
    Keywords: Algorithms Demand Design Guide Logistics Methodology Model Optimization Rail-rail transshipment Review Risk-management Simulation Solve Strategies Supply chain Taxonomy
    Abstract: Supply chain networks are typical examples of complex systems. Thereby, making decisions in such systems remains a very hard issue. To assist decision makers in formulating the appropriate strategies, robust tools are needed. Pure optimization models are not appropriate for several reasons. First, an optimization model cannot capture the dynamic behavior of a complex system. Furthermore, most common practical problems are very constrained to be modeled as simple tractable models. To fill in the gap, hybrid optimization/simulation techniques have been applied to improve the decision-making process. In this paper we explore the near-full spectrum of optimization methods and simulation techniques. A review and taxonomy were performed to give an overview of the broad field of optimization/simulation approaches applied to solve supply chain problems. Since the possibilities of coupling them are numerous, we launch a discussion and analysis that aims at determining the appropriate framework for the studied problem depending on its characteristics. Our study may serve as a guide for researchers and practitioners to select the suitable technique to solve a problem and/or to identify the promising issues to be further explored.
    Thematic Areas: Ciência da computação Computer science (all) Computer science (miscellaneous) Computer science, information systems Electrical and electronic engineering Engenharias iii Engenharias iv Engineering (all) Engineering (miscellaneous) Engineering, electrical & electronic General computer science General engineering General materials science Materials science (all) Materials science (miscellaneous) Telecommunications
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: abdelali.elaroudi@urv.cat
    Author identifier: 0000-0001-9103-7762
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://ieeexplore.ieee.org/document/8993766
    Papper original source: Ieee Access. 8 31710-31732
    APA: El Raoui, H; Oudani, M; Alaoui, AE (2020). Coupling Soft Computing, Simulation and Optimization in Supply Chain Applications: Review and Taxonomy. Ieee Access, 8(), 31710-31732. DOI: 10.1109/ACCESS.2020.2973329
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1109/ACCESS.2020.2973329
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2020
    Publication Type: Journal Publications
  • Keywords:

    Computer Science (Miscellaneous),Computer Science, Information Systems,Engineering (Miscellaneous),Engineering, Electrical & Electronic,Materials Science (Miscellaneous),Telecommunications
    Algorithms
    Demand
    Design
    Guide
    Logistics
    Methodology
    Model
    Optimization
    Rail-rail transshipment
    Review
    Risk-management
    Simulation
    Solve
    Strategies
    Supply chain
    Taxonomy
    Ciência da computação
    Computer science (all)
    Computer science (miscellaneous)
    Computer science, information systems
    Electrical and electronic engineering
    Engenharias iii
    Engenharias iv
    Engineering (all)
    Engineering (miscellaneous)
    Engineering, electrical & electronic
    General computer science
    General engineering
    General materials science
    Materials science (all)
    Materials science (miscellaneous)
    Telecommunications
  • Documents:

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