8 citations · 17 across the 9 of their papers we have counts for
10 papers
Dynamic Dispatching for Time-Sensitive Blood Sample Collection and Delivery
Arash Dehghan, Aliaa Alnaggar, Mucahit Cevik +1
Hospitals and diagnostic laboratories rely on couriers to collect blood samples from geographically dispersed collection centres and deliver them for analysis before their short vi…
Joint Matching and Pricing for Crowd-shipping with In-store Customers
Arash Dehghan, Mucahit Cevik, Merve Bodur +1
This paper examines the use of in-store customers as delivery couriers in a centralized crowd-shipping system, targeting the growing need for efficient last-mile delivery in urban…
Dynamic AGV Task Allocation in Intelligent Warehouses
Arash Dehghan, Mucahit Cevik, Merve Bodur
This paper explores the integration of Automated Guided Vehicles (AGVs) in warehouse order picking, a crucial and cost-intensive aspect of warehouse operations. The booming AGV ind…
Neural Approximate Dynamic Programming for the Ultra-fast Order Dispatching Problem
Arash Dehghan, Mucahit Cevik, Merve Bodur
Same-Day Delivery (SDD) services aim to maximize the fulfillment of online orders while minimizing delivery delays but are beset by operational uncertainties such as those in order…
An Enhanced Approximate Dynamic Programming Approach to On-demand Ride Pooling
Arash Dehghan, Mucahit Cevik, Merve Bodur
Ride-pooling services have been growing in popularity, increasing the need for efficient and effective operations. The main goal of ride-pooling services is to maximize the number…
Improved -GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning
Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar
Generative Adversarial Networks (GANs) have gained significant attention in several computer vision tasks for generating high-quality synthetic data. Various medical applications i…
Linear programming-based solution methods for constrained partially observable Markov decision processes
Robert K. Helmeczi, Can Kavaklioglu, Mucahit Cevik
Constrained partially observable Markov decision processes (CPOMDPs) have been used to model various real-world phenomena. However, they are notoriously difficult to solve to optim…
A multi-objective constrained POMDP model for breast cancer screening
Robert K. Helmeczi, Can Kavaklioglu, Mucahit Cevik +1
Breast cancer is a common and deadly disease, but it is often curable when diagnosed early. While most countries have large-scale screening programs, there is no consensus on a sin…
A Multiobjective Approach for Sector Duration Optimization in Stereotactic Radiosurgery Treatment Planning
Oylum Şeker, Mucahit Cevik, Merve Bodur +2
Sector duration optimization (SDO) is a problem arising in treatment planning for stereotactic radiosurgery on Gamma Knife. Given a set of isocenter locations, SDO aims to select c…
Simultaneous optimization of isocenter locations and sector duration in radiosurgery
Mucahit Cevik, Dionne Aleman, Young Lee +5
Stereotactic radiosurgery is an effective technique to treat brain tumors for which several inverse planning methods may be appropriate. We propose an integer programming model to…