Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 4 of 4
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Overview Of Optimization Problems Regarding Emergency Organization Allocation Based On Mathematical Programming, Cejun Cao, Congdong Li
Overview Of Optimization Problems Regarding Emergency Organization Allocation Based On Mathematical Programming, Cejun Cao, Congdong Li
Journal of System Simulation
Abstract: To improve the utilization of human resources in large-scale natural disasters and reduce various losses, how to use mathematical programming approach to optimize emergency organization allocation strategy is the currently urgent and critical issue. A decision framework or conceptual model for emergency organization allocation optimization is proposed. The current status of mathematical programming model for emergency organization allocation is presented from the perspective of task sequence and objective quantity. An overview on the exact and heuristic algorithm to solve the proposed model is conducted. Potential issues for in-depth study with respect to simulation and modeling of emergency organization allocation …
Evaluating Flexibility Metrics On Simple Temporal Networks With Reinforcement Learning, Hamzah I. Khan
Evaluating Flexibility Metrics On Simple Temporal Networks With Reinforcement Learning, Hamzah I. Khan
HMC Senior Theses
Simple Temporal Networks (STNs) were introduced by Tsamardinos (2002) as a means of describing graphically the temporal constraints for scheduling problems. Since then, many variations on the concept have been used to develop and analyze algorithms for multi-agent robotic scheduling problems. Many of these algorithms for STNs utilize a flexibility metric, which measures the slack remaining in an STN under execution. Various metrics have been proposed by Hunsberger (2002); Wilson et al. (2014); Lloyd et al. (2018). This thesis explores how adequately these metrics convey the desired information by using them to build a reward function in a reinforcement learning …
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …
The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Physician scheduling is the assignment of physicians to perform different duties in the hospital timetable. In this paper, the goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We present a mathematical programming model to represent the problem as a bi-objective optimization problem. Three different methods based on ε–Constraint Method, Weighted-Sum Method and HillClimbing algorithm are proposed. These methods were tested on a real case from the Surgery Department of a large local government hospital, as well as on randomly generated problem instances. The strengths and weaknesses of the …