Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Eos — An Evolutionary and Ecosystem Research Platform
BT Technology Journal
A New Genetic Local Search Algorithm for Graph Coloring
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
iOpt: A Software Toolkit for Heuristic Search Methods
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Localizer: a Modeling Language for Local Search
INFORMS Journal on Computing
An Object-Oriented Framework for Local Search Heuristics
TOOLS '98 Proceedings of the Technology of Object-Oriented Languages and Systems
A multi-agent organizational framework for coevolutionary optimization
Transactions on Petri nets and other models of concurrency IV
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The Heuristic Search Framework (HSF) is a Java object-oriented framework allowing to easily implement single solution algorithms such as Local Search, population-based algorithms such as Genetic Algorithms, and hybrid methods being a combination of the two. The main idea in HSF is to break down any of these heuristic algorithms into a plurality of constituent parts. Thereafter, a user can use this library of parts to build existing or new algorithms. The main motivation behind HSF is to provide a "well-designed" framework dedicated to heuristic methods in order to offer representation of existing methods and to retain flexibility to build new ones. In addition, the use of the infra-structure of the framework avoid the need to re-implement parts that have already been incorporated in HSF and reduces the code necessary to extend existing components.