Constraint-Based Scheduling
Edge Finding for Cumulative Scheduling
INFORMS Journal on Computing
Not-First and not-last detection for cumulative scheduling in O(n3 log n)
INAP'05 Proceedings of the 16th international conference on Applications of Declarative Programming and Knowledge Management
A new o(n2log n) not-first/not-last pruning algorithm for cumulative resource constraints
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Explaining the cumulative propagator
Constraints
Timetable edge finding filtering algorithm for discrete cumulative resources
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Limited discrepancy search revisited
Journal of Experimental Algorithmics (JEA)
Filtering algorithms for discrete cumulative problems with overloads of resource
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
A quadratic edge-finding filtering algorithm for cumulative resource constraints
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
The multi-inter-distance constraint
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
A scalable sweep algorithm for the cumulative constraint
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
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This paper presents new Edge Finding algorithm for discrete cumulative resources, i.e. resources which can process several activities simultaneously up to some maximal capacity C. The algorithm has better time complexity than the current version of this algorithm: O(kn log n) versus O(kn2) where n is number of activities on the resource and k is number of distinct capacity demands. Moreover the new algorithm is slightly stronger and it is able to handle optional activities. The algorithm is based on the Θ-tree - a binary tree data structure which already proved to be very useful in filtering algorithms for unary resource constraints.