Automating branch-and-bound for dynamic programs
PEPM '08 Proceedings of the 2008 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation
Learning from the Past to Dynamically Improve Search: A Case Study on the MOSP Problem
Learning and Intelligent Optimization
Minimizing the maximum number of open stacks by customer search
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Lock-free parallel dynamic programming
Journal of Parallel and Distributed Computing
Improving combinatorial optimization: extended abstract
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We give a dynamic-programming solution to the problem of minimizing the maximum number of open stacks. Starting from a call-based dynamic program, we show a number of ways to improve the dynamic-programming search, preprocess the problem to simplify it, and determine lower and upper bounds. We then explore a number of search strategies for reducing the search space. The final dynamic-programming solution is, we believe, highly effective.