CLAHC - custom late acceptance hill climbing first results on TSP

Clay, Sylvain; Mousin, Lucien; Veerapen, Nadarajen; Jourdan, Laetitia

Type de document :

Communication dans un congrès avec actes

DOI :

10.1145/3449726.3463129

Titre :

CLAHC - custom late acceptance hill climbing first results on TSP

Auteur(s) :

Clay, Sylvain [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Mousin, Lucien [Auteur]
Université Catholique de Lille - Faculté de gestion, économie et sciences [UCL FGES]
Operational Research, Knowledge And Data [ORKAD]
Veerapen, Nadarajen [Auteur]

Operational Research, Knowledge And Data [ORKAD]
Jourdan, Laetitia [Auteur]

Operational Research, Knowledge And Data [ORKAD]

Titre de la manifestation scientifique :

GECCO '21 Companion: Genetic and Evolutionary Computation Conference Companion

Ville :

Lille

Pays :

France

Date de début de la manifestation scientifique :

2021-07-10

Titre de la revue :

GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Éditeur :

ACM

Date de publication :

2021-07

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]

Résumé en anglais : [en]

The Late Acceptance Hill Climbing heuristic is a Hill Climbing algorithm that uses a record of the history of objective values of previously encountered solutions in order to decide whether to accept a new solution. ...
Lire la suite >The Late Acceptance Hill Climbing heuristic is a Hill Climbing algorithm that uses a record of the history of objective values of previously encountered solutions in order to decide whether to accept a new solution. Literature has shown that Late Acceptance Hill Climbing is generally better at not getting stuck in local optima because of the history. In this paper, we propose and investigate a simple, yet effective, modification to Late Acceptance Hill Climbing, where we change how values in the history are replaced. In our tests, referring to the Traveling Salesman Problem, we analyze the behavior of the proposed approach for different history sizes. We also show that the simple change in the algorithm allows the heuristic to find better solutions than the original one on most of the instances tested.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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