Incremental graph evaluation (attribute grammar)
Incremental graph evaluation (attribute grammar)
Incremental attribute evaluation: a flexible algorithm for lazy update
ACM Transactions on Programming Languages and Systems (TOPLAS)
Integrating pointer variables into one-way constraint models
ACM Transactions on Computer-Human Interaction (TOCHI)
The Amulet Environment: New Models for Effective User Interface Software Development
IEEE Transactions on Software Engineering
Incremental evaluation of computational circuits
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Lessons learned about one-way, dataflow constraints in the Garnet and Amulet graphical toolkits
ACM Transactions on Programming Languages and Systems (TOPLAS)
Applications of Constraint Programming
CP '95 Proceedings of the First 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
LOCAL++: A C++ Framework for Local Search Algorithms
TOOLS '99 Proceedings of the Technology of Object-Oriented Languages and Systems
Localizer
Inferring Constraint Types in Constraint Programming
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
ARMS — Application of AI and OR Methods to Resource Management
BT Technology Journal
Maintaining Longest Paths Incrementally
Constraints
Retractable contract network for empowerment in workforce scheduling
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Intelligent Resource Allocation---Solutions and Pathways in a Workforce Planning Problem
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
Kangaroo: an efficient constraint-based local search system using lazy propagation
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Characterization and automation of matching-based neighborhoods
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
HYPERION: a recursive hyper-heuristic framework
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Constraint propagation as the core of local search
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
International Journal of Applied Metaheuristic Computing
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Heuristic Search techniques are known for their efficiency and effectiveness in solving NP-Hard problems. However, there has been limited success so far in constructing a software toolkit which is dedicated to these methods and can fully support all the stages and aspects of researching and developing a system based on these techniques. Some of the reasons for that include the lack of problem modelling facilities and domain specific frameworks which specifically suit the operations of heuristic search, tedious code optimisations which are often required to achieve efficient implementations of these methods, and the large number of available algorithms - both local search and population-based - which make it difficult to implement and evaluate a range of techniques to find the most efficient one for the problem at hand. The iOpt Toolkit, presented in this article, attempts to address these issues by providing problem modelling facilities well-matched to heuristic search operations, a generic framework for developing scheduling applications, and a logically structured heuristic search framework allowing the synthesis and evaluation of a variety of algorithms. In addition to these, the toolkit incorporates interactive graphical components for the visualisation of problem and scheduling models, and also for monitoring the run-time behaviour and configuring the parameters of heuristic search algorithms.