Decomposing Metaheuristic Operations
Non-exhaustive local search methods are fundamental tools in applied branches of computing such as operations research, and in other applications of optimisation. These problems have proven stubbornly resistant to attempts to find generic meta-heuristic toolkits that are both expressive and computationally efficient for the large problem spaces involved. This paper complements recent work on functional abstractions for local search by examining three fundamental operations on the states that characterise allowable and/or intermediate solutions. We describe how three fundamental operations are related, and how these can be implemented effectively as part of a functional local search library.
KeywordsSearch Optimisation Stochastic Combinatorial
The authors would like to thank Tim Sheard for all his advice in the final stages of writing this paper.
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