An Efficient Outpatient Scheduling Approach

Outpatient scheduling is considered as a complex problem. Efficient solutions to this problem are required by many health care facilities. Our previous work in Role-Based Collaboration (RBC) has shown that the group role assignment problems can be solved efficiently. Making connections between these two kinds of problems is meaningful. This paper proposes an efficient approach to outpatient scheduling by specifying a bidding method and converting it to a group role assignment problem. The proposed approach is validated by conducting simulations and experiments with randomly generated patient requests for available time slots. The major contribution of this paper is an efficient outpatient scheduling approach making automatic outpatient scheduling practical. The exciting result is due to the consideration of outpatient scheduling as a collaborative activity and the creation of a qualification matrix in order to apply the group role assignment algorithm. Note to practitioners -As the “Age Wave” approaches, health care facilities are becoming relatively scarce worldwide compared with what are demanded. The varying availability, requirements, and preferences of both facilities and outpatients make the problem of scheduling outpatient appointments on health care facilities extremely challenging. Traditional manually operated scheduling systems based on phone calls are out of date although they are still widely used due to lack of new effective scheduling systems. To solve such a problem requires an efficient Web-based system to schedule the appointments instantly in order to make full use of those expensive and critical facilities. It is able to optimize concerned performance objectives in a clinical environment. The proposed approach provides a technical foundation for efficient Web-based scheduling systems, which can be applied directly to not only outpatient scheduling in the health care sector, but also in some other real-world scheduling applications

Modelling and Solving Decentralized and Dynamic Aircraft Landing Scheduling Problems

Aircraft landing problem (ALP) is considered as a scheduling problem where aircrafts are sequenced and allocated with appropriate time slots. In this thesis ALP problem is investigated where several constraints such as aircraft’s landing time windows, minimum separation time and position shifting constraints are taken into consideration. Existing approaches such as optimized solution based methods and heuristic methods to tackle different aspects of the problem are reviewed, and a static mathematical model is studied. The mathematical model is solved and verified using random data generated from simulation. The data are generated based on Pierre Elliott Trudeau International Airport (YUL) in Montreal, Quebec, Canada as well as from relevant data base library. AnyLogictm software was used to simulate aircraft landing operations in a runway environment. An agent based simulation was designed to include the dynamic event of aircrafts arrivals to the runway system. In the agent based system, an iterative bidding framework is used to generate flight landing schedule in a decentralized environment. In the decentralized environment, we consider each flight as a self-interest agent competing with other flights to get the most appropriate landing time. The efficiency of the decentralized approach is also studied. The results of the decentralized approach are compared with the centralized ALP solution. The results show that the agent based solution approach is able to generate reasonable landing comparing to optimal aircraft landing schedule from the centralized ALP model

Decentralized and Dynamic Home Health Care Resource Scheduling Using an Agent-Based Model

The purpose of this thesis is to design an agent-based scheduling system, simulated in a dynamic environment that will reduce home healthcare service costs. The study focuses on situations where a health care agency needs to assign home visits among a group of independent healthcare practitioners. Each practitioner has different skill sets, time constraints, and cost structures, given the nature, time and location of each home visit. Each expects reasonable payment commensurate with their skill levels as well as the costs incurred. The healthcare agency in turn needs all planned visits performed by qualified practitioners while minimizing overall service costs. Decisions about scheduling are made both before and during the scheduling period, requiring the health care agency to respond to unexpected situations based on the latest scheduling information. This problem is examined in a multi-agent system environment where practitioners are modeled as self-interested agents. The study first analyzes the problem for insights into the combinatorial nature of such a problem occurring in a centralized environment, then discusses the decentralized and dynamic challenges. An iterated bidding mechanism is designed as the negotiation protocol for the system. The effectiveness of this system is evaluated through a computational study, with results showing the proposed multi-agent scheduling system is able to compute high quality schedules in the decentralized home healthcare environment. Following this, the system is also implemented in a simulation model that can accommodate unexpected situations. We presents different simulation scenarios which illustrate the process of how the system dynamically schedules incoming visits, and cost reduction can be observed from the results