Memetic Solver

Memetic strategy for solving irreversably ill-conditioned parametric inverse problems.

License	The Apache License, Version 2.0
GroupId	io.github.jswk.ms
ArtifactId	ms
Last Version	0.0.4-RELEASE
Release Date	Jan 7, 2021
Type	pom
Description	Memetic Solver Memetic strategy for solving irreversably ill-conditioned parametric inverse problems.
Project URL	https://github.com/jswk/ms
Source Code Management	http://github.com/jswk/ms/tree/master

Download ms

Filename	Size
ms-0.0.4-RELEASE.pom	7 KB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/io.github.jswk.ms/ms/ -->
<dependency>
    <groupId>io.github.jswk.ms</groupId>
    <artifactId>ms</artifactId>
    <version>0.0.4-RELEASE</version>
    <type>pom</type>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/io.github.jswk.ms/ms/
implementation 'io.github.jswk.ms:ms:0.0.4-RELEASE'

Gradle Kotlin

// https://jarcasting.com/artifacts/io.github.jswk.ms/ms/
implementation ("io.github.jswk.ms:ms:0.0.4-RELEASE")

Apache Buildr

'io.github.jswk.ms:ms:pom:0.0.4-RELEASE'

Apache Ivy

<dependency org="io.github.jswk.ms" name="ms" rev="0.0.4-RELEASE">
  <artifact name="ms" type="pom" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='io.github.jswk.ms', module='ms', version='0.0.4-RELEASE')
)

Scala SBT

libraryDependencies += "io.github.jswk.ms" % "ms" % "0.0.4-RELEASE"

Leiningen

[io.github.jswk.ms/ms "0.0.4-RELEASE"]

Dependencies

There are no dependencies for this project. It is a standalone project that does not depend on any other jars.

Project Modules

• ms-core
• ms-examples

Memetic Strategy for solving irreversibly ill-conditioned inverse parametric problems

The Memetic Strategy (MS) is a framework for solving irreversibly ill-conditioned inverse parametric problems. Such problems arise in numerous practical applications, including medical diagnosis, hydrocarbon prospecting and defectoscopy. MS attempts to detect areas of insensitivity of the objective function of such problems, giving practitioners in the field more insight into the particular instance of a problem.

The strategy consists of several phases: global, local and shape approximation. The global phase determines separated sets of attraction of the insensitivity regions (i.e. lowlands). Then, the local phase proceeds to probe the set of attraction, in preparation for the lowland shape approximation.

Modules

The functionality is placed in module ms-main. Examples of how to use the library are shown in ms-examples.

Usage

Add the following dependency to your pom.xml:

<dependency>
    <groupId>io.github.jswk.ms</groupId>
    <artifactId>ms-core</artifactId>
    <version>some-version</version>
</dependency>

Upgrading dependencies

Run ./mvnw versions:display-dependency-updates -U for dependencies updates and ../mvnw versions:display-plugin-updates -U for plugin updates.

Releasing

Run ./mvnw clean deploy -Pgpg -Dchangelist=-RELEASE -Drevision=<version>.

Versions

Version
0.0.4-RELEASE Jan 7, 2021
0.0.3-RELEASE Jan 6, 2021
0.0.2-RELEASE Jan 5, 2021
0.0.1-RELEASE Jan 5, 2021