Andere Kunden interessierten sich auch für
![CENTRALIZED AND DECENTRALIZED DISTRIBUTION STORAGE SYSTEMS]( "CENTRALIZED AND DECENTRALIZED DISTRIBUTION STORAGE SYSTEMS")
CENTRALIZED AND DECENTRALIZED DISTRIBUTION STORAGE SYSTEMS44,99 €![Optimal Decision-Making for Catastrophic Earthquakes]( "Optimal Decision-Making for Catastrophic Earthquakes")
Optimal Decision-Making for Catastrophic Earthquakes44,99 €![Hierarchical Risk Analysis of Complex Systems]( "Hierarchical Risk Analysis of Complex Systems")
Hierarchical Risk Analysis of Complex Systems44,99 €![Urban Transportation Planning Decision Making]( "Urban Transportation Planning Decision Making")
Urban Transportation Planning Decision Making32,99 €![A DEA Decision Making Model for Higher Education Funding]( "A DEA Decision Making Model for Higher Education Funding")
A DEA Decision Making Model for Higher Education Funding32,99 €![Research Challenges in Modeling and Simulation for Engineering Complex Systems]( "Research Challenges in Modeling and Simulation for Engineering Complex Systems")
Research Challenges in Modeling and Simulation for Engineering Complex Systems66,99 €![MATERIALS AND DECISION SUPPORT SYSTEMS IN THE NUCLEAR POWER INDUSTRY]( "MATERIALS AND DECISION SUPPORT SYSTEMS IN THE NUCLEAR POWER INDUSTRY")
MATERIALS AND DECISION SUPPORT SYSTEMS IN THE NUCLEAR POWER INDUSTRY27,99 €
Over the last several decades, computer simulations
have been widely utilized to model and analyze
complex systems at low costs and risks. Although
simulation can represent physical systems
realistically, it is a descriptive tool without the
capability of suggesting better solutions. However,
it can be complemented by incorporating optimization
routines. The most challenging problem is that
large-scale simulation models normally take a
considerable amount of computer time to execute so
that the number of solution evaluations needed by
most optimization algorithms is not feasible within a
reasonable time frame. This book, therefore, provides
a highly efficient evolutionary simulation-based
decision making procedure which can be applied in
real-time management situations. We have used this
novel simulation-optimization technique to study
several disaster response problems. The methodologies
provided herein should be useful to professionals and
researchers in the fields of industrial engineering
and operations research. The applications in disaster
response management should help emergency managers
and personnel to gain insights into several
significant response problems.
have been widely utilized to model and analyze
complex systems at low costs and risks. Although
simulation can represent physical systems
realistically, it is a descriptive tool without the
capability of suggesting better solutions. However,
it can be complemented by incorporating optimization
routines. The most challenging problem is that
large-scale simulation models normally take a
considerable amount of computer time to execute so
that the number of solution evaluations needed by
most optimization algorithms is not feasible within a
reasonable time frame. This book, therefore, provides
a highly efficient evolutionary simulation-based
decision making procedure which can be applied in
real-time management situations. We have used this
novel simulation-optimization technique to study
several disaster response problems. The methodologies
provided herein should be useful to professionals and
researchers in the fields of industrial engineering
and operations research. The applications in disaster
response management should help emergency managers
and personnel to gain insights into several
significant response problems.