jMetal is designed as an object-oriented Java-based framework that is specially aimed at the development, experimentation, and study of metaheuristics for solving multi-objective optimization problems. Metal stands for Metaheuristic Algorithms in Java,
jMetal provides a rich set of classes which can be used as the building blocks of multi-objective metaheuristics; taking advantage of code-reusing, the algorithms share the same base components, such as implementations of genetic operators and density estimators, thus facilitating the development of new multi-objective algorithms.
A number of multi-objective metaheuristics have been implemented using jMetal, and many problems usually included in performance studies are currently available in the framework.
jMetal also provides quality indicators to performance assessing as well as a set of utilities that help in carrying out experimental studies.
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jMetal Product Key is a framework for performing metaheuristic optimization. It has a set of classes that can be used to construct a metaheuristic, including genetic operators, fitness functions, and search algorithms. These metaheuristics are encapsulated in what is called a jMetal Torrent Download algorithm, and can be coupled with an optimization or search engine. The jMetal framework has four main classes: 1. Genetic operator (class Gen); 2. Search engine (class SE); 3. Object oriented fitness functions (class FO); 4. Object oriented objective functions (class OB).
The Genetic operators (class Gen) perform certain actions on the population and are parameterized.
Each search engine can perform any of the search algorithms used in metaheuristics (e.g., evolutionary algorithms, stochastic algorithms, and ant systems), though the jMetal framework includes an evolved search engine named LeGPS.
The jMetal framework can be used in performance studies. It is provided with a set of utilities to carry out such studies.
Open-source License: GNU Public License
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jMetal is an object-oriented Java-based framework that supports the design and the implementation of new multi-objective metaheuristic algorithms.
The jMetal framework includes classes to represent individuals in the population, to carry out reproduction, crossover, and mutation of these individuals, and a class to represent the solution obtained by the algorithm.
jMetal supports two ways of choosing the multi-objective
algorithm: as a user, through the definition of «algorithm factories» that can be plugged in the framework, or as a developer, through a set of abstract classes that can be used to implement new algorithms.
If we include some libraries, we have the possibility to optimize the performance of the algorithms. The distribution of the classes is very simple, so the source code of the framework is very easy to understand.
jMetal allows the easy incorporation of new classes or algorithms. The framework is fully extensible, with no constraints on the number of individuals or the number of components that the algorithm may have.
With jMetal, it is very simple to solve a multi-objective problem, and to design new metaheuristic algorithms.
jMetal is written in Java and has been tested on Java 5 and 6, with the Sun HotSpot JVM and the IBM J9 VM.
The complete jMetal source code is available for download at and is part of the jMetal project.
jMetal is an object-oriented Java-based framework that supports the design and the implementation of new multi-objective metaheuristic algorithms. The jMetal framework includes classes to represent individuals in the population, to carry out reproduction, crossover, and mutation of these individuals, and a class to represent the solution obtained by the algorithm.
jMetal supports two ways of choosing the multi-objective algorithm: as a user, through the definition of «algorithm factories» that can be plugged in the framework, or as a developer, through a set of abstract classes that can be used to implement new algorithms.
If we include some libraries, we have the possibility to optimize the performance of the algorithms. The distribution of the classes is very simple, so the source code of the framework is very easy to understand.
jMetal allows the easy incorporation of new classes or algorithms. The framework is fully extensible, with no constraints on the number of individuals or the number of components that the algorithm may have.
With jMetal, it
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jMetal is a metaheuristic framework for solving multi-objective optimization problems written in Java and aimed at the development, experimentation, and study of heuristic metaheuristic techniques for solving multi-objective optimization problems.
The framework allows the development of a new algorithm to solve a specific problem and the associated implementation of the desired metaheuristic.
In addition, jMetal provides a set of classes that can be reused as building blocks to develop new algorithms. This way, the same components are used by different algorithms to achieve a new method.
The jMetal framework includes a set of algorithms to solve multi-objective problems that have been implemented using the Java programming language and therefore, are cross-platform compatible.
A set of problems have been included in the framework, many of which are usually included in performance studies.
The jMetal framework contains a set of quality indicators and utilities to help with performance assessments and the design of experiments.
jMetal Structure:
The jMetal framework is designed as a set of classes that are managed through three different modules.
The jMetal Abstract Base Class module defines the base classes for the implementation of metaheuristics.
The jMetal Support Classes module contains the implementations of the different metaheuristics already included in the framework.
The jMetal Helpers module contains utility classes used in the framework to solve and carry out experiments.
The jMetal framework has been divided into three main modules:
The jMetal Abstract Base Class module defines the base classes for the implementation of metaheuristics. It also contains the classes that will be used to define the different individuals of the metaheuristic algorithms (e.g., operators, fitness functions, and populations).
The jMetal Support Classes module contains the implementations of the different metaheuristics already included in the framework. The modules implementing the different metaheuristics provide the methods that will be used by each individual of the algorithm.
The jMetal Helpers module contains the utility classes used in the framework to solve and carry out experiments. The classes include those used to solve the objective functions, carry out the experiments, store the collected data, and also analyze and plot the collected data.Japan Inc uses the term «Economic Miracle» to refer to the period in the late 1980’s when the country saw its economy gain strength following Japan’s defeat in the second world war.
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What’s New in the JMetal?
jMetal is an object-oriented Java framework that facilitates the development and implementation of multi-objective metaheuristics. The jMetal metaheuristic library is an object-oriented framework that allows programmers to create metaheuristics with a simplified programming model. The framework is designed as an object-oriented library, so that it can be used with object-oriented programming languages such as Java.
Based on these features, jMetal provides a broad set of metaheuristic components, so that metaheuristics are designed on top of this framework with a simple programming model.
jMetal Metaheuristic Components:
jMetal has a variety of components that can be used as building blocks to build new metaheuristics. These components, as their name suggests, deal with the characteristics of the metaheuristics implemented with jMetal.
There are two components provided in jMetal that define the Genetic Operators and Density Estimators.
1. Genetic Operator
The genetic operator deals with the process of generating new offspring, which is the heart of any evolutionary algorithm. The genetic operator is the core of any metaheuristic. Thus, the genetic operator of any metaheuristic has been implemented as a generic component in jMetal.
2. Density Estimator
The density estimator component estimates the density of the current population, which is the set of individuals created by the genetic operator. This component is the heart of any metaheuristic that implements an approximation method, such as NSGA-II. It is the most expensive component of a metaheuristic and it is often the limiting factor in the performance of the metaheuristic.
jMetal currently provides implementations of some of the most important multi-objective metaheuristics in the literature. These algorithms are based on the metaheuristic components provided in jMetal.
The most widely used of these algorithms are DMOE, MOEA/D, HGTD, and MOEA/D++. jMetal implements the first four of these algorithms, while MOEA/D++ has been implemented as part of jMetal.
In addition to these algorithms, jMetal has been the base for the development of several new algorithms. A small number of these new algorithms have been released as jMetal components, and the best of them is probably MOEA/C.
jMetal is not only a Java framework, but it also has a C component that can be used in the development of C-based metaheuristics.
jMetal Utility Features:
jMetal also provides a set of utility features that help in performance analysis, comparing different multi-objective metaheuristics, and carrying out experimental studies. These features are as follows:
1. Performance Analysis Features
jMetal provides a number of performance indicators that can be used for evaluating the performance of a metahe
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System Requirements For JMetal:
Supported OS: Windows 7/Vista/XP/2000
Processor: Intel® Pentium®4 3.0 GHz/AMD Athlon64 3.0 GHz or higher
Memory: 512 MB RAM
Hard Drive: 10 GB free space
Video Card:
DirectX: DirectX 9.0c
Video Driver: Vista or higher
WDDM compatible graphics card
Screen Resolution: 1024×768
Network: Broadband Internet connection
Vidalia Plugins:
None
Size: 4
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