Abstract
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.
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Tamir, D.E., King, C.R., McKenney, M. (2012). Improving the Performance of Constructive Multi-Start Search Using Record-Keeping. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science(), vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_19
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DOI: https://doi.org/10.1007/978-3-642-31087-4_19
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