Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that mitigate each of these curses. To handle the state-space explosion, we introduce “tabular linear functions” that generalize tile-coding and linear value functions. Action space complexity is reduced by replacing compl...

In most stochastic inventory models, such as continuous review models and periodic review models, it has been assumed that the stockout period during a cycle is small enough to be neglected so that the average number of cycles per year can be approximated as D/Q, where D is the average annual demand and Q is the order quantity. This assumption makes the problem more tactable, but it should not ...

In most stochastic inventory models, such as continuous review models and periodic review models, it has been assumed that the stockout period during a cycle is small enough to be neglected so that the average number of cycles per year can be approximated as D/Q, where D is the average annual demand and Q is the order quantity. This assumption makes the problem more tactable, but it should not ...

This paper examines the interactions between routing and inventory-management decisions in a two-level supply chain consisting of a cross-docking warehouse and N retailers. Retailer demand is stochastic; i.e., normally distributed and independent across retailers and over time. Travel times are fixed between pairs of system sites. Every m time periods, system inventory is replenished at the war...

1. Summary 2 1.1 Uncertainty of input parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Availability of input parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Commodity handling patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Classification of methods . . . . . . . . . . . . . ....

Inventory-routing problems (IRPs) arise in vendor-managed inventory systems. They require jointly solving a vehicle routing problem and an inventory management problem. Whereas the solutions they yield tend to benefit the vendor and customers, solving IRPs solely based on cost considerations may lead to inconveniences to both parties. These are related to the fleet size and vehicle load, to the...

Title of Dissertation: ONLINE INVENTORY REPLENISHMENT AND FLEET ROUTING DECISIONS UNDER REAL-TIME INFORMATION Ricardo Giesen, Ph.D., 2007 Dissertation Directed By: Professor Hani S. Mahmassani, Civil and Environmental Engineering Department Logistics managers rely on increasingly sophisticated technologies to track demand and associated inventories, allowing rapid response to meet anticipated d...

We consider a single item Production-Inventory-Routing problem with a single producer/supplier and multiple retailers. Inventory management constraints are considered both at the producer and at the retailers, following a vendor managed inventory approach, where the supplier monitors the inventory at retailers and decides on the replenishment policy for each retailer. We assume a constant produ...

This article provides an introduction to approximation algorithms in stochastic optimization models arising in various application domains, including central areas of operations management, such as scheduling, facility location, vehicle routing problems, inventory and supply chain management and revenue management. Unfortunately, these models are very hard to solve to optimality both in theory ...

I this paper, we present a solution approach for the inventory-routing problem. The inventory-routing problem is a variation of the vehicle-routing problem that arises in situations where a vendor has the ability to make decisions about the timing and sizing of deliveries, as well as the routing, with the restriction that customers are not allowed to run out of product. We develop a two-phase a...