José A. Sepúlveda

Multi-objective simulation optimization for a cancer treatment center

The 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, compared to the existing solution.

The use of simulation for process improvement in a cancer treatment center

This work addresses experience with a simulation model of a full service cancer treatment center. The objective was to analyze patient flow throughout the unit, evaluate the impact of alternative floor layouts, using different scheduling options and to analyze resources and patient flow requirements of a new building. The simulation model provided strong justification to relocate the centers laboratory and pharmacy as well as identifying changes in scheduling procedures that would allow a 30% increase in patient throughput with the same resources. The new building analysis identified a waiting room area that was too small for the increased patient flow.

Emerging issues in healthcare simulation

Despite the size and importance of the health care industry, simulation is less prevalent in health care than in other fields such as manufacturing, logistics, and military applications. Yet simulation clearly has the potential to play a role in health care decision-making at many levels. The purpose of this panel is to discuss some of the issues that practioners must be aware of in order to tap the potential of simulation in the health care arena. The panelists have extensive experience in health care and the use of simulation in that environment. They have provided statements outlining several key issues for achieving success in current and future health care simulation projects. These will serve as the starting point for discussion at the conference.

Multi-response simulation optimization using stochastic genetic search within a goal programming framework

This study presents a new approach to solve multi-response simulation optimization problems. This approach integrates a simulation model with a genetic algorithm heuristic and a goal programming model. The genetic algorithm technique offers a very flexible and reliable tool able to search for a solution within a global context. This method was modified to perform the search considering the mean and the variance of the responses. In this way, the search is performed stochastically, and not deterministically like most of the approaches reported in the literature. The goal programming model integrated with the genetic algorithm and the stochastic search present a new approach able to lead a search towards a multi-objective solution.

The use of simulation and design of experiments for productivity improvement in the sawmill industry

This work presents a discrete event simulation model of an important sawmill in Chile. This model was used to perform a bottleneck analysis of the wood process and to propose, based on these results, alternatives that would yield to an improvement in the process productivity. Different alternatives were simulated and the results obtained were used to perform a full factorial design in order to select the combination of factors that have the most important impact in the process productivity. The implementation of these improvement measures could increase the wood production up to a 25%.

Simulation of range safety for the NASA space shuttle

Purpose – The main objective of this paper is to introduce the development of a decision‐support environment for a complex problem: space range safety. Simulation modeling can provide a good environment to support range safety managers.Design/methodology/approach – The paper describes the different models and the processes to find the different knowledge sources. In addition, it investigates statistically the most important factors. This will help determine emergency management procedures and sources of variability.Findings – This case study provides guidance and an example to follow for other problems in aerospace (in particular new the analysis of new vehicles). There are important factors to consider in order to implement risk management in National Aeronautics and Space Administration.Research limitations/implications – There are several limitations; blast and debris effects need to be added.Practical implications – First, it provides a guide in order to persuade managers of the utilization of decisio...

A distributed simulation approach for modeling and analyzing systems of systems

Certain business objectives cannot be met without the interaction and communication between different systems. An interesting concept called system of systems (SoS), which aims to describe this interaction between systems has been gaining attention in the last few years. In this paper an extensive review of the literature is performed to capture the main characteristics associated to this concept in order to propose a new, more complete definition. This paper also proposes the use of distributed simulation through the high level architecture (HLA) rules to model and simulate systems of systems. We illustrate our idea with two different examples; a simplified supply chain network of a computer assembly and an aircraft initial sizing scenarios. The paper concludes with a discussion of some of the significant advantages distributed simulation could offer over traditional simulation for the analysis of such complex systems

A simulator to improve waiting times at a medical imaging center

Medical Imaging Centers (MIC) are critical units in every hospital or medical center because they are an important step in generating a patient¿s diagnostic. This paper shows a simulator designed to facilitate the development of simulation studies of MIC, which departs from traditional modeling because it uses a pull paradigm for the patients. A group technology approach was used to minimize the number of objects in the simulator, which includes objects that have the functionality of the equipments and processes found in these facilities, so that the analyst only needs to provide the parameters of the center. All the data is provided to the simulator through a Graphic User Interface (GUI), requiring no programming capacities. As an application of the simulator, an example is provided where the simulator is used to improve the waiting times and equipment rate of utilization at a research hospital in Chile.

Disaster and prevention management for the NASA shuttle during lift‐off

Purpose – The main objective of this paper is to introduce the development of a decision‐support environment for space range safety. Simulation modeling can provide a good environment to support disaster and prevention management.Design/methodology/approach – The paper describes the different models and the processes to find the different knowledge sources. This will help determine emergency management procedures.Findings – This case study provides guidance and an example to follow for other problems in aerospace. There are important factors to consider in order to implement risk management in NASA.Research limitations/implications – There are several limitations; first debris effects need to be added.Practical implications – First, the paper provides a guide in order to persuade managers of the utilization of decision support systems based on geographical information systems. Second, it shows that there is open source software which can be used and integrated to make a more comprehensive environment. Val...

Implementing the high level architecture in the Virtual Test Bed

The virtual test bed (VTB) is a prototype of a virtual engineering environment to study operations of current and future space vehicles, spaceports, and ranges. The high-level architecture (HLA) as defined by the Department of Defense (DoD), is the main environment. The VTB/HLA implementation described here represents different systems that interact in the simulation of a space shuttle liftoff. This example implementation displays the collaboration of a simplified version of the space shuttle simulation model and a simulation of the launch scrub evaluation model. Spaceports and ranges are complex systems. This VTB framework is a collaborative computing environment that integrates in a seamless fashion simulation models that represent the different stages in the lifecycle of a complex system. A complex system is a non-linear system of systems whose interactions bring together interesting emergent properties that are very difficult to visualize and/or study by using the traditional approach of decomposition.