A large number of problems in production planning and scheduling, location, transportation,
finance, and engineering design require that decisions be made in the presence of …

This paper discusses Supply Chain Network (SCN) design problem under uncertainty, and
presents a critical review of the optimization models proposed in the literature. Some …

What is reinforcement learning? How is reinforcement learning different from stochastic
optimization? And finally, can it be used for applications to quantitative finance for my current …

Most relevant decisions to be made by market agents within an energy market involve a
significant level of data uncertainty. For agents to make informed decisions within such a …

A complete and accessible introduction to the real-world applications of approximate
dynamic programming With the growing levels of sophistication in modern-day operations, it …

Literature on supply chain management (SCM) covers several disciplines and is growing
rapidly. This paper firstly aims at extracting the essence of SCM and advanced planning in …

This study reviews the papers that pertain to the hydrogen supply chain network design
(HSCND) models published in scientific journals. A few drawbacks (eg, the treatment of …

This study proposes two location–allocation models for handling uncertainty in the strategic
planning of hospital networks. The models aim to inform how the hospital networking system …

This article presents a methodology for planning new water resources infrastructure
investments and operating strategies in a world of climate change uncertainty. It combines a …

To be efficient, logistics operations in e‐commerce require warehousing and transportation
resources to be aligned with sales. Customer orders must be fulfilled with short lead times to …