In this paper, we develop a stylized partially observed Markov decision process (POMDP) framework, to study a dynamic pricing problem faced by sellers of fashion-like goods. We consider a retailer that plans to sell a given stock of items during a finite sales season. The objective of the retailer is to dynamically price the product in a way that maximizes expected revenues. Our model brings to...

This paper proposes a model for dynamic pricing that combines knowledge of production capacity and existing commitments, reasoning about uncertainty and learning of market conditions in an attempt to optimise expected profits. In particular, the market conditions are represented as a set of probabilities over the success rate of product prices, and those prices are learned online as the market ...

Smart parking is becoming more and an integral part of smart city initiatives. Utilizing managing areas a challenging task as space often limited, finding empty spaces are hard citizens want to park their vehicles close preferred places. This becomes worse in important/posh major metropolitan cities during rush hour. Due unavailability proper management system, have roam around lot order find s...

We consider a context-based dynamic pricing problem of online products, which have low sales. Sales data from Alibaba, major global retailer, illustrate the prevalence low-sale products. For these existing single-product algorithms do not work well due to insufficient samples. To address this challenge, we propose policies that concurrently perform clustering over product demand and set individ...

This paper is devoted to the development of heuristics for dynamic pricing problem. A discrete time model on fixed horizon proposed. It applicable products that satisfy two properties: 1) product value expires at a certain predetermined date, and 2) consumers demand most single unit product. type structure allows deriving simple system recursive equations optimal prices using programming techni...

Objectives: A Smart Parking System with Dynamic Pricing Model is proposed and developed for vehicle parking management using real time data collected from five popular hotspots in the city of Chennai. Methods: The model polynomial regression algorithm Python language. vital parameters considered training a are: traffic data, geological distance, day, peak hour or not, weekend not especially, nu...