HEAL 

Sim# aims to port the concepts used in SimPy (https://pypi.python.org/pypi/simpy) to the .NET world. It is implemented in C# and builds on the .NET Framework 4.5 / .NET Standard 2.0. Sim# uses an efficient... More information

HEAL.Attic is a serialization and persistence framework for .NET. It serializes and deserializes complete object graphs and uses Google Protocol Buffers for compact storage.

MultiKeyCollections adds MultiKeyDictionary classes which, as the name implies, are dictionaries that can be accessed by more than one key. These can be sliced to obtain representations with less keys. A slice... More information

TreesearchLib is a framework for modeling optimization problems that are to be solved by constructive heuristics. It includes a number of algorithms: exhaustive depth-first and breadth-first search, limited... More information

A .NET wrapper for the splitting conic solver (SCS).

A .NET wrapper for the splitting conic solver (SCS).

Repository implementations for RDBMS access. Provides default implementations for abstract base classes and interfaces for domain oriented CRUD access to relational databases. Provides repositories for Data... More information

Code snippets and extension methods that are shared by internal libraries or are reoccurring in multiple projects. The contents of this project are restricted to target standard .NET namespaces.

Domain repository based access to Excel files. Utilizes EPPlus for formula calculation prior to data reads. Currently only supports only read access.

Interfaces, abstract implementations and enumerated types for business entities impllemented as POCOs that are required for the data access libraries.

Interfaces and abstract base implementations for DataAccess.

Provides parser and wrappers for the National Instruments DIAdem file types DAT and TDM.

Description

Package Description

Package Description

Package Description

Fit and evaluate nonlinear regression models.

Composable heuristic optimization algorithms, operators, search spaces and built-in problems.

Core abstractions for HeuristicLib.

Experimental features of HeuristicLib.