Managing demand uncertainty in supply chain planning

By Anshuman Gupta, Costas D. Maranas. Computers and Chemical Engineering, 2003

571 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/1bb5a2edab72b860c44c93bfa223ae2bafb01a60

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Citations in the corpus

Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices (2004, methodology): “Three distinct methods are frequently mentioned for representing uncertainty (Liu & Sahinidis, 1997; Gupta & Maranas, 2003): first, the distribution-based approach, where the normal distribution with specified mean and standard deviation is widely invoked for modeling uncertain demands and/or…”
A multi-objective stochastic programming approach for supply chain design considering risk (2008, methodology): “Petkov and Maranas (1997), Gupta and Maranas (2003) and Gupta et al. (2000) incorporated the uncertain demands as multivariatenormal distributions.”
Mathematical programming models for supply chain production and transport planning (2010, background): “Gupta and Maranas (2003) adopted McDonald and Karimi’s model (1997) as the basis of their work, and proposed transformation in a stochastic model which considers demand uncertainty.”
Capacity and material requirement planning modelling by comparing deterministic and fuzzy models (2008, background): “Gupta and Maranas ( 2003 ) and Sodhi ( 2005 ) addressed the problem of supply chain production planning under demand uncertainty using a stochastic programming-based approach.”
Models for production planning under uncertainty: A review ☆ (2006, background): “Also, Gupta and Maranas (2003) address the problem of tactical planning of supply chains under demand uncertainty using a stochastic programming based approach.”
Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming (2019, unknown): “51], and supply chain management [52-58].”
Towards resilient supply chains: Uncertainty analysis using fuzzy mathematical programming (2009, background): “a p p i a k i a h p a f ( c u f d t p i t t al., 1981; Kall and Wallace, 1994; Loeve, 1963; Charnes and ooper, 1959; Gupta and Maranas, 2003; Gupta et al., 2000; itra et al., 2008) does not require all decisions to be feasile for every outcome of the random variables, but require easibility with at ”
The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand (2010, methodology): “Supply chain production planning consists of the coordination and the integration of key business activities carried out from the procurement of raw materials to the distribution of finished products to the customer (Gupta and Maranas, 2003).”
A simulation based optimization approach to supply chain management under demand uncertainty (2004, background): “Gupta and Maranas (2003) further generalize their approach to the multi-period case.”