Reducing time in an emergency room via a fast-track
WSC '95 Proceedings of the 27th conference on Winter simulation
Introduction to simulation in health care
WSC '96 Proceedings of the 28th conference on Winter simulation
A generalised simulation system to support strategic resource planning in healthcare
Proceedings of the 29th conference on Winter simulation
Proceedings of the 30th conference on Winter simulation
The use of simulation for process improvement in a cancer treatment center
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 2
Proceedings of the 32nd conference on Winter simulation
Genetic Algorithms
Proceedings of the 35th conference on Winter simulation: driving innovation
A survey of data resources for simulating patient flows in healthcare delivery systems
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation-based multi-objective optimization of a real-world scheduling problem
Proceedings of the 38th conference on Winter simulation
Computers and Industrial Engineering
A web-based simulation optimization system for industrial scheduling
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 40th Conference on Winter Simulation
Simulation-based optimization of a complex mail transportation network
Proceedings of the 40th Conference on Winter Simulation
A provably convergent heuristic for stochastic bicriteria integer programming
Journal of Heuristics
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
A Lexicographic Nelder-Mead simulation optimization method to solve multi-criteria problems
Computers and Industrial Engineering
Two metaheuristics for multiobjective stochastic combinatorial optimization
SAGA'05 Proceedings of the Third international conference on StochasticAlgorithms: foundations and applications
Hi-index | 0.00 |
This paper presents a case study application of a cancer treatment center facility. A simulation model was created and integrated to a multi-objective optimization heuristic developed by the authors with the purpose of finding the best combination of control variables that optimize the performance of four different objectives related to the system. The results obtained show that the implementation of the proposed solution could improve the four objectives in comparison to the existing solution.