Design of Iterated Local Search Algorithms
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
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PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
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Computers and Operations Research
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Bringing order into the neighborhoods: relaxation guided variable neighborhood search
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Journal of Heuristics
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Expert Systems with Applications: An International Journal
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UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Operations Research Letters
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We consider the neighborhood tree induced by alternating the use of different neighborhood structures within a local search descent. We investigate the issue of designing a search strategy operating at the neighborhood tree level by exploring different paths of the tree in a heuristic way. We show that allowing the search to 'backtrack' to a previously visited solution and resuming the iterative variable neighborhood descent by 'pruning' the already explored neighborhood branches leads to the design of effective and efficient search heuristics. We describe this idea by discussing its basic design components within a generic algorithmic scheme and we propose some simple and intuitive strategies to guide the search when traversing the neighborhood tree. We conduct a throughout experimental analysis of this approach by considering two different problem domains, namely, the Total Weighted Tardiness Problem (SMTWTP), and the more sophisticated Location Routing Problem (LRP). We show that independently of the considered domain, the approach is highly competitive. In particular, we show that using different branching and backtracking strategies when exploring the neighborhood tree allows us to achieve different trade-offs in terms of solution quality and computing cost.