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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

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Variable Neighborhood Search (VNS)

Metaheuristic based on the systematic exploration of different neighborhood structures to escape local optima and find globally optimal solutions.

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Shaking

Random perturbation phase in VNS using a neighborhood structure to generate a starting solution far from the current local optimum.

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Local Search

Iterative improvement phase applied after shaking to converge toward a local optimum in the neighborhood of the perturbed solution.

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Variable Neighborhood Descent (VND)

Deterministic variant of VNS sequentially exploring different neighborhood structures until no further improvement is possible.

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Reduced VNS

Simplified variant of VNS applying local search directly to the current solution without an intermediate shaking phase.

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General VNS

Extended version of VNS incorporating advanced neighborhood change strategies and exploration-exploitation balancing mechanisms.

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Skewed VNS

VNS variant introducing a bias to favor solutions distant from the reference solution, useful for avoiding premature convergence.

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Neighborhood Change

Mechanism determining when and how to switch between different neighborhood structures based on improvement or stagnation criteria.

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Perturbation Control

Adaptive strategy controlling the intensity of the shaking phase based on the quality of found solutions and the number of iterations without improvement.

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Neighborhood Sequence

Predefined or dynamic order of exploring different neighborhood structures influencing the convergence and diversification of the search.

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Variable Neighborhood Decomposition Search (VNDS)

Hybridization of VNS with decomposition techniques solving sub-problems on variable parts of the solution.

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Multi-start VNS

Approach executing VNS from multiple different initial solutions to increase the probability of finding the global optimum.

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Parallel VNS

Parallel implementation of VNS simultaneously exploiting multiple neighborhood structures or executing independent searches in parallel.

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Hybrid VNS

Combination of VNS with other metaheuristics such as simulated annealing, genetic algorithms, or tabu search to improve performance.

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Adaptive VNS

VNS variant dynamically adapting parameters and neighborhood structures based on performance history during the search.

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Multi-objective VNS

Extension of VNS to multi-objective optimization problems managing a set of Pareto-optimal solutions with specific diversification mechanisms.

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Dynamic Neighborhood

Approach where neighborhood structures evolve dynamically during the search according to the characteristics of the explored solution landscape.

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