Reza Refaei Afshar

Eindhoven University of Technology | TUE · Department of Industrial Engineering and Innovation Sciences

Real time bidding is one of the most popular ways of selling impressions in online advertising, where online ad publishers allocate some blocks in their websites to sell in online auctions. In real time bidding, ad networks connect publishers and advertisers. There are many available ad networks for publishers to choose from. A possible approach fo...

On-time delivery and low service costs are two important performance metrics in warehousing operations. This paper proposes a Deep Reinforcement Learning (DRL) based approach to solve the online Order Batching and Sequence Problem (OBSP) to optimize these two objectives. To learn how to balance the trade-off between two objectives, we introduce a B...

On-time delivery and low service costs are two important performance metrics in warehousing operations. This paper proposes a Deep Reinforcement Learning (DRL) based approach to solve the online Order Batching and Sequence Problem (OBSP) to optimize these two objectives. To learn how to balance the trade-off between two objectives, we introduce a B...

This paper reports on the first international competition on AI for the traveling salesman problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21). The TSP is one of the classical combinatorial optimization problems, with many variants inspired by real-world applications. This first competition asked the parti...

Reinforcement Learning and recently Deep Reinforcement Learning are popular methods for solving sequential decision making problems modeled as Markov Decision Processes. RL modeling of a problem and selecting algorithms and hyper-parameters require careful considerations as different configurations may entail completely different performances. Thes...

Dynamic pricing problem is difficult due to the highly dynamic environment and unknown demand distributions. In this paper, we propose a Deep Reinforcement Learning (DRL) framework, which is a pipeline that automatically defines the DRL components for solving a Dynamic Pricing problem. The automated DRL pipeline is necessary because the DRL framewo...

We study how web publishers should set their floor prices in order to maximize expected revenues when they have access to two selling mechanisms, namely an ad exchange and header bidding, in order to sell impressions on the real-time bidding market. We consider the publisher’s problem under incomplete information, propose bandit-type algorithms, an...

Water distribution networks have shown an increased rate of failure due to material deterioration. In this paper, we apply a Recurrent Neural Hawkes Process model to learn the failure intensity function of water pipes. The failure intensity function is learned based on two components: the base failure rate that is determined by the unique pipe prof...

This paper proposes a Deep Reinforcement Learning (DRL) approach for solving knapsack problem. The proposed method consists of a state aggregation step based on tabular reinforcement learning to extract features and construct states. The state aggregation policy is applied to each problem instance of the knapsack problem, which is used with Advanta...

High turnover of online advertising and especially real time bidding makes this ad market very attractive to beneficiary stakeholders. For publishers, it is as easy as placing some slots in their webpages and sell these slots in the available online auctions. It is important to determine which online auction market to send their slots to. Based on...

A high percentage of online advertising is currently performed through real time bidding. Impressions are generated once a user visits the websites containing empty ad slots, which are subsequently sold in an online ad exchange market. Nowadays, one of the most important sources of income for publishers who own websites is through online advertisin...

This paper propose a new approach to predict spreading behavior of conventions. Conventions in our case are verbal i.e. phrases used by many people for a new purpose regarding a social issue. We study usage of some conventions in Twitter popularized among Persian speaking users. We show that the number of tweets that contain a convention phrase in...