Abstract Neighborhood search heuristics like local search and its variants are some of the most popular approaches to solve discrete optimization problems of moderate to large size. Apart from tabu search, most of these heuristics are memoryless. In this paper we intro-duce a new neighborhood search heuristic that makes effective use of memory structures in a way that is different from tabu search. We report computational experiments with this heuristic on the traveling salesperson problem and the subset sum problem. Keywords: Discrete Optimization, Neighborhood, Local Search, Tabu Search
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Paper provided by University of Groningen, Research Institute SOM (Systems, Organisations and Management) in its series Research Report with number
00A47.