Journal ArticleDOI
A computationally efficient simulation-based optimization method with region-wise surrogate modeling for stochastic inventory management of supply chains with general network structures
Wenhe Ye,Fengqi You +1 more
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TLDR
This work proposes an efficient framework for reducing the total operation cost while satisfying the service level constraints and is able to solve general supply chain problems with the multi-sourcing capability, asynchronous ordering, uncertain demand and stochastic lead time.About:
This article is published in Computers & Chemical Engineering.The article was published on 2016-04-06. It has received 40 citations till now. The article focuses on the topics: Simulation-based optimization & Service level.read more
Citations
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Journal ArticleDOI
Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming
Chao Ning,Fengqi You +1 more
TL;DR: This paper identifies fertile avenues for future research that focuses on a closed-loop data-driven optimization framework, which allows the feedback from mathematical programming to machine learning, as well as scenario-based optimization leveraging the power of deep learning techniques.
Journal ArticleDOI
Overview of Surrogate Modeling in Chemical Process Engineering
Journal ArticleDOI
A typology and literature review on stochastic multi-echelon inventory models
TL;DR: The typology is used to classify and review the extensive research of multi-echelon inventory management under uncertain demand and clusters of model assumptions, research goals and applied methodologies are identified.
Journal ArticleDOI
From process control to supply chain management: An overview of integrated decision making strategies
TL;DR: An overview of integrated decision-making strategies is provided and recent advances in the area are reviewed, highlighting promising works as well as the main challenges that have yet to be overcome.
Journal ArticleDOI
The role of simulation and optimization methods in supply chain risk management: Performance and review standpoints
Josenildo Brito de Oliveira,Josenildo Brito de Oliveira,Mingzhou Jin,Renato da Silva Lima,John E. Kobza,José Arnaldo Barra Montevechi +5 more
TL;DR: The results revealed a key methodological disconnection involving risk management phases, simulation and optimization methods, which highlights the limitations of several models to represent the dynamics and complexity of the risks in supply chains, particularly on real-world/real-time applications.
References
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Book
Simulation Modeling and Analysis
Averill M. Law,W. David Kelton +1 more
TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.
Journal ArticleDOI
The design and analysis of computer experiments
TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Book
Supply Chain Management: Strategy, Planning and Operations
Sunil Chopra,Peter Meindl +1 more
TL;DR: In this paper, the authors present a framework to analyze the supply chain performance and predict demand and supply in an e-commerce e-business environment, and discuss the role of cross-functional drivers in the process.
Book
Interpolation of Spatial Data: Some Theory for Kriging
TL;DR: This chapter discusses the role of asymptotics for BLPs, and applications of equivalence and orthogonality of Gaussian measures to linear prediction, and the importance of Observations not part of a sequence.
Journal ArticleDOI
Design and analysis of computer experiments
Sonja Kuhnt,David M. Steinberg +1 more
TL;DR: The included papers present an interesting mixture of recent developments in the field as they cover fundamental research on the design of experiments, models and analysis methods as well as more applied research connected to real-life applications.
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