Open AccessJournal Article
Supply Chain: Crisp and Fuzzy Aspects
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In this paper, a survey presents crisp and fuzzy models developed for the supply chain (SC) developed for manufacturing and service industries, with reference to different aspects of an SC system, with respect to different fuzzy models for different SC systems and compare them with related crisp models.Abstract:
This survey presents crisp and fuzzy models developed for the Supply Chain (SC). To this end, fuzzy concepts are first
briefly reviewed. Then the structure of a supply chain system is explained. Recent challenges and ideas on these systems
are also surveyed. Then, with reference to different aspects of an SC system, we classify the recent fuzzy models developed
for different SC systems and compare them with related crisp models. Applications of the SC in manufacturing and service
industries are investigated in each case.read more
Citations
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Fuzzy optimization for supply chain planning under supply, demand and process uncertainties
TL;DR: A fuzzy mathematical programming model for supply chain planning which considers supply, demand and process uncertainties, formulated as a fuzzy mixed-integer linear programming model where data are ill-known and modelled by triangular fuzzy numbers is proposed.
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Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management
TL;DR: A fuzzy integrated multi-period and multi-product production and distribution model in supply chain is developed in terms of fuzzy programming and the solution is provided by genetic optimization (genetic algorithm).
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A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment
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Select supplier-related issues in modelling a dynamic supply chain: potential, challenges and direction for future research
TL;DR: A broad review of the main approaches to supplier-related issues especially supplier selection, supplier-buyer relationships, supplier buyer flexibility in relationships in a dynamic supply chain is provided in this article.
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Stochastic multi-objective production-distribution network design using simulation-based optimization
TL;DR: In this paper, an optimization methodology that combines a multi-objective genetic algorithm (MOGA) and simulation is proposed to optimize not only the structure of the production-distribution network but also its operation strategies and related control parameters.
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