Critical Event Tabu Search for Multidimensional Knapsack Problems

Glover, Fred; Kochenberger, Gary A.

doi:10.1007/978-1-4613-1361-8_25

Cited by 123 publications

(88 citation statements)

References 9 publications

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“…A number of papers in the literature [25], [26], [33], [41], [42], [43], [44] make use of an add and (or) drop phase to either construct, improve or repair solutions to the multidimensional 0-1 knapsack problem. These techniques more often than not use a utility-weight value to score and sort the objects in order of their relative efficiency.…”

Section: A Genetic Programming Hyper-heuristic For the Multidimenmentioning

confidence: 99%

A genetic programming hyper-heuristic for the multidimensional knapsack problem

et al. 2014

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Abstract-Hyper-heuristics are a class of high-level search techniques which operate on a search space of heuristics rather than directly on a search space of solutions. Early hyperheuristics focussed on selecting and applying a low-level heuristic at each stage of a search. Recent trends in hyper-heuristic research have led to a number of approaches being developed to automatically generate new heuristics from a set of heuristic components. This work investigates the suitability of using genetic programming as a hyper-heuristic methodology to generate constructive heuristics to solve the multidimensional 0-1 knapsack problem. A population of heuristics to rank knapsack items are trained on a subset of test problems and then applied to unseen instances. The results over a set of standard benchmarks show that genetic programming can be used to generate constructive heuristics which yield human-competitive results.

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Section: A Genetic Programming Hyper-heuristic For the Multidimenmentioning

confidence: 99%

A genetic programming hyper-heuristic for the multidimensional knapsack problem

et al. 2014

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“…We apply our heuristics on a set of 18 instances proposed by Glover and Kochenberger (1996) with n ∈ [100; 2500] and m ∈ [15; 100]. Table 8 reports the results obtained by our 3 algorithms.…”

Section: Some Experiments With Larger Instancesmentioning

confidence: 99%

“…Several of those are metaheuristic-based algorithms like tabu search (see for instance Glover and Kochenberger (1996), and Hanafi and Fréville (1998)), and genetic algorithm (Chu and Beasley (1998)). …”

Section: Introductionmentioning

confidence: 99%

An iterative variable-based fixation heuristic for the 0-1 multidimensional knapsack problem

Wilbaut

Salhi

Hanafi

2009

European Journal of Operational Research

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“…This situation suggests further directions of research: First, the (1 + 7)-ES scheme with pure random mutation resembles some sort of Tabu search [7,8], and so might be greatly improved by adding some memory to it, either deterministically, like in standard Tabu search, or stochastically, as proposed in [15,13].…”

Section: Mutations and Population Sizementioning

confidence: 99%