Related papers: Emergency Centre Organization and Automated Triage…
State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and…
This paper introduces an improved Electronic Stability Program for cars that can deal with the sudden burst of a tyre. The Improved Electronic Stability Program (IESP) is based on a fuzzy logic algorithm. The IESP collects data from the…
We study the optimal method for rationing scarce resources through a queue system. The designer controls agents' entry into a queue and their exit, their service priority -- or queueing discipline -- as well as their information about queue…
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for…
Recently, the combination of machine learning (ML) and simulation is gaining a lot of attention. This paper presents a novel application of ML within the simulation to improve patient flow within an emergency department (ED). An ML model…
In this paper, we propose a Q-learning based decision-making framework to improve the safety and efficiency of Autonomous Vehicles when they encounter other maliciously behaving vehicles while passing through unsignalized intersections. In…
In this study, we provided a scheduling procedure which is a combination of machine learning and mathematical programming that minimizes the waiting time of higher priority outpatients. Outpatients who request for appointment in healthcare…
This paper proposes a bi-level optimization framework to coordinate Automated Guided Vehicle (AGV) flexible operations in smart independent warehouses, addressing the critical challenge of balancing high-throughput order fulfillment with…
Automated drug dispensing systems (ADDSs) are increasingly in demand in today's pharmacies, primarily driven by the growing ageing population. Recognizing the practical challenges faced by pharmacies implementing ADDSs, this study aims to…
We study a make-to-order system with a finite set of customers. Production is stochastic with a nonlinear dependence between the ordered quantity and the production rate. Customers may have to queue until their turn arrives, and therefore…
One area of research in multi-agent path finding is to determine how replanning can be efficiently achieved in the case of agents being delayed during execution. One option is to reschedule the passing order of agents, i.e., the sequence in…
We study an optimal server partition and customer assignment problem for an uncapacitated FCFS queueing system with heterogeneous types of customers. Each type of customers is associated with a Poisson arrival, a certain service time…
We study a continuous-time, infinite-horizon dynamic bipartite matching problem. Suppliers arrive according to a Poisson process; while waiting, they may abandon the queue at a uniform rate. Customers on the other hand must be matched upon…
In this paper, a collision avoidance system is presented to detect red light running and warn nearby vehicles and pedestrians in real time in order to prevent possible accidents. No complex infrastructure-based solution such as those based…
In queueing systems, effective scheduling algorithms are essential for optimizing performance. Optimal scheduling for the M/G/k queue has been explored in the heavy traffic limit, but much remains unknown in the intermediate load regime. In…
Identification of critical or weak buses for a given operating condition is an important task in the load dispatch centre. It has become more vital in view of the threat of voltage instability leading to voltage collapse. This paper…
We introduce two new optimization models for the dispatch of ambulances. The first model, called the ambulance selection problem, is used when an emergency call arrives to decide whether an ambulance should be dispatched for that call, and…
The optimization of complex medical appointment scheduling remains a significant operational challenge in multi-center healthcare environments, where clinical safety protocols and patient logistics must be reconciled. This study proposes…
The electroencephalogram (EEG) is one of the most precious technologies to understand the happenings inside our brain and further understand our body's happenings. Automatic prediction of oncoming seizures using the EEG signals helps the…
We address a single server queue control problem (QCP) in heavy traffic originating from Lee and Weerasinghe (2011). The state process represents the offered waiting time, the customer arrival has a state-dependent intensity, and the…