Improving the 0–1 Multi Dimensional Knapsack Lower Bounds with Tabu Search
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چکیده
Due to the problems intrinsic difficulty, which leads to intractable computation time for larger instances, several heuristics have been used to solve it, including simulated annealing, tabu search, genetic algorithms, and many other population based algorithms. Large instances (n = 500, m = 30 from OR-Library), for which exact methods fail to prove the optimum, have thus been tackled successfully, i.e. lowerbounds with small gap to the fractional optimum value were obtained by these incomplete methods.
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An Empirical Study of Tabu Search for the MOKP
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