Engineering Commons^™

Essays On Perioperative Services Problems In Healthcare, Amogh S. Bhosekar

All Dissertations

One of the critical challenges in healthcare operations management is to efficiently utilize the expensive resources needed while maintaining the quality of care provided. Simulation and optimization methods can be effectively used to provide better healthcare services. This can be achieved by developing models to minimize patient waiting times, minimize healthcare supply chain and logistics costs, and maximize access. In this proposal, we study some of the important problems in healthcare operations management. More specifically, we focus on perioperative services and study scheduling of operating rooms (ORs) and management of necessary resources such as staff, equipment, and surgical instruments. We …

Optimal Scheduling Of Aircraft Test And Evaluation Fleets To Balance Availability For Testing And Training, Sarah E. Hoops

Theses and Dissertations

The 96th Test Wing at Eglin Air Force Base manually schedules a fleet of approximately 26 aircraft to conduct a range of missions over a one-to-two year planning period. This study automates the scheduling process, does so in a manner that optimizes multiple planning goals related to aircraft availability for training, and provides the 96th Test Wing with a software tool for the implementation that can be used by operational analysts within the command. We formulate the scheduling problem as a multiobjective, nonlinear, binary integer math program that seeks to maximize both the lowest percent of time any aircraft is …

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

A Study Of Scheduling Problems With Sequence Dependent Restrictions And Preferences, Nitin Srinath

All Dissertations

In some applications like fabric dying, semiconductor wafer processing, and flexible manufacturing, the machines being used to process jobs must be set up and serviced frequently. These setup processes and associated setup times between jobs often depend on the jobs and the sequence in which jobs are placed onto machines. That is, the scheduling of jobs on machines must account for the sequence-dependent setup times as well. These setup times can be a major factor in operational costs. In fabric dyeing processes, the sequence in which jobs are processed is also important for quality, i.e., there is a strong preference …

Design And Development Of A Simulation System For Scheduling In Cloud Manufacturing Based On Microservice Architecture, Yongkui Liu, Ming Zeng, Lin Zhang, Jinwei Guo, Siyang Yuan, Yaoyao Ping

Journal of System Simulation

Abstract: In view of the lack of the low coupling and highly extensible cloud manufacturing scheduling simulation system, that leads to inconvenience of the performance test on scheduling algorithms, a scalable cloud manufacturing scheduling model with the scheduling goal of the minimization of cost and completion time and the maximization of quality of service is proposed. A micro-service architecture based cloud manufacturing scheduling simulation system is designed and developed, which realizes the functions of system management, resource management, task management and simulation management, and has the characteristics of flexible autonomy, stability and scalability. The simulation system facilitates the …

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …

Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang

Journal of System Simulation

Abstract: In order to improve the utilization of the network resources of the FlexRay bus, the network is optimized for static segment scheduling. The FlexRay communication mechanism is analyzed, the message model is established and the calculation method of bandwidth loss is derived, while considering the protocol overhead and network idling, taking the number of static frames and the length of the static frame payload as design variables, the overall optimal packaging scheme is obtained by solving this multi-objective optimization problem. This solution is finally applied to the vehicle chassis integrated control system for simulation analysis and verification. The results …

Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu

Research Collection School Of Computing and Information Systems

This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …