Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Introduction to algorithms
Software caching vs. prefetching
Proceedings of the 3rd international symposium on Memory management
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Cache Diversity in Genetic Algorithm Design
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference
Computer Architecture, Fourth Edition: A Quantitative Approach
Computer Architecture, Fourth Edition: A Quantitative Approach
Information Processing Letters
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
Caching in the TSP Search Space
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Optimal time-space tradeoff in probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Time space tradeoffs in GA based feature selection for workload characterization
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Compression of individual sequences via variable-rate coding
IEEE Transactions on Information Theory
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State-space search redundancy, that is, multiple explorations of the same state, is an inherent problem in many heuristic search algorithms. It is prevalent in constructive multi-start algorithms. Record-keeping mechanisms, however, can minimize redundancy and enable exploiting time/space tradeoffs. This paper investigates the utility of record-keeping procedures in the context of Iterative Hill Climbing applied to the Traveling Salesperson Problem using several restart mechanisms including Greedy Randomized Adaptive Search, and Greedy Enumeration. Record-keeping methods such as unbounded memory, dedicated memory, and cache memory, as well as a novel "book-keeping" method utilizing a Bloom filter are investigated. Experiments performed using TSPLIB benchmarks and random TSP instances with 100 cities show that under the above mentioned restart and record-keeping mechanisms the IHC produces competitive results. In addition, the research shows that record-keeping, in specific Bloom filters, can considerably improve both the time performance of IHC and the quality of solutions produced.