A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study compares MAPF and MARL algorithms for warehouse automation.
We aim to predict and explain service failures in supply-chain networks, more precisely among last-mile pickup and delivery services to customers. We analyze a dataset of 500,000 services using (1) supervised classification with Random Forests, and (2) Association Rules. Our classifier reaches an average sensitivity of…
This paper explores the possibility of near-optimally solving multi-agent, multi-task NP-hard planning problems with time-dependent rewards using a learning-based algorithm. In particular, we consider a class of robot/machine scheduling problems called the multi-robot reward collection problem (MRRC). Such MRRC problem…
Study predicts purchasing decisions of online food delivery customers.
Deep Q-learning optimizes same-day delivery with vehicles and drones.
Extends Black model to include commodities with potential negative prices.
Paper introduces a new pricing method for electricity swaps and options.
This paper tackles fair same-day delivery service by optimizing regional service rates.
Boosting algorithms improve delivery time prediction in postal services.
Paper predicts IVF pregnancy rates from basic patient info.
The paper tackles ride-hailing fleet repositioning with a calibrated demand approach.
An evolutionary game model analyzes e-commerce and traditional retail trends during the pandemic.
Kriging predicts futures prices by accounting for trends and bid-ask spreads.
We study superhedging of contingent claims with physical delivery in a discrete-time market model with convex transaction costs. Our model extends Kabanov's currency market model by allowing for nonlinear illiquidity effects. We show that an appropriate generalization of Schachermayer's robust no arbitrage condition im…
Rapid growth in delivery and freight transportation is increasing in urban areas; as a result the use of delivery trucks and light commercial vehicles is evolving. Major cities can use traffic counting as a tool to monitor the presence of delivery vehicles in order to implement intelligent city planning measures. Class…
Preterm birth is the most common cause of neonatal death. Current diagnostic methods that assess the risk of preterm birth involve the collection of maternal characteristics and transvaginal ultrasound imaging conducted in the first and second trimester of pregnancy. Analysis of the ultrasound data is based on visual i…
A make-your-mind-up option is an American derivative with delivery lags. We show that its put option can be decomposed as a European put and a new type of American-style derivative. The latter is an option for which the investor receives the Greek Theta of the corresponding European option as the running payoff, and de…
We propose a multi-factor polynomial framework to model and hedge long-term electricity contracts with delivery period. This framework has several advantages: the computation of forwards, risk premium and correlation between different forwards are fully explicit, and the model can be calibrated to observed electricity …
The paper models natural gas futures prices and volatility, using Monte Carlo and reinforcement learning.
We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increments process for the low-frequency dynamics, and model the la…
Deep learning model reduces food waste by stabilizing online food delivery supply chains.
Study uses few-shot learning to analyze claims and arguments in German debate on arms deliveries.
Advertisement (abbreviated ad) options are a recent development in online advertising. Simply, an ad option is a first look contract in which a publisher or search engine grants an advertiser a right but not obligation to enter into transactions to purchase impressions or clicks from a specific ad slot at a pre-specifi…
This handbook translates lead time analysis into R code.
This article presents an empirical study of thirteen derivative markets for commodity and financial assets. It compares the statistical properties of futures contracts's daily returns at different maturities, from 1998 to 2010 and for delivery dates up to 120 months. The analysis of the fourth first moments of the dist…
Proposes SDCN to integrate structural information into deep clustering.
The paper extends the market price of risk for electricity swap contracts, incorporating jump risk.
We present an end-to-end framework for solving the Vehicle Routing Problem (VRP) using reinforcement learning. In this approach, we train a single model that finds near-optimal solutions for problem instances sampled from a given distribution, only by observing the reward signals and following feasibility rules. Our mo…
This paper applies reactor theory to supply chain management.
In the first section, this report analyses Nuclear Power Plants (NPPs) in the context of megaprojects, explaining why they are often delivered over budget and late. In the second section, the report discusses how Small Modular Reactors (SMRs) might address these issues. Megaprojects are extremely risky and often implem…
New model optimizes oil product distribution via pipelines.
The purpose of this paper is to identify the immediate and future retailer response to wholesale stockouts. We perform a statistical analysis of historical customer order and delivery data of a local tool wholesaler and distributor, whose customers are retailers, over a period of four years. We investigate the effect o…
The paper proposes a survival model to optimize mobile notification delivery times.
There is a need for affordable, widely deployable maternal-fetal ECG monitors to improve maternal and fetal health during pregnancy and delivery. Based on the diffusion-based channel selection, here we present the mathematical formalism and clinical validation of an algorithm capable of accurate separation of maternal …
We propose an elementary model to price European physical delivery swaptions in multicurve setting with a simple exact closed formula. The proposed model is very parsimonious: it is a three-parameter multicurve extension of the two-parameter Hull-White (1990) model. The model allows also to obtain simple formulas for a…
Generative modeling on metric graphs using neural optimal transport
The paper models user-advertiser interactions using point processes.
Improved prediction of polymer morphology through machine learning and simulations.
Adversarial attacks degrade DRL-based EV energy management systems.
Develops a new model for day-ahead electricity prices using ambit fields.
LOLA uses LLMs to optimize content delivery, outperforming traditional methods.
New algorithm learns uncertainty for edge devices.
A new method for energy-efficient file delivery in small cell networks.
One of the peculiarities of power and gas markets is the delivery mechanism of forward contracts. The seller of a futures contract commits to deliver, say, power, over a certain period, while the classical forward is a financial agreement settled on a maturity date. Our purpose is to design a Heath-Jarrow-Morton framew…
Copulas model cross-product effects in intraday power markets.
Develops a new trading strategy for renewable producers to manage price volatility.
The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the p…
Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc for matching restaurants to customers. In these online to offline service problems, individuals who are respo…