Article

Ant-Based Hyper-Heuristics for the Movie Scene Scheduling Problem

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Artificial Intelligence and Soft Computing: 20th International Conference, ICAISC 2021, Virtual Event, June 21–23, 2021, Proceedings, Part II

Pages 342 - 353

https://doi.org/10.1007/978-3-030-87897-9_31

Published: 20 June 2021 Publication History

Abstract

The paper provides a study of the use of hyper-heuristics on the movie scene scheduling problem. In particular, the paper extends the definition of the movie scene scheduling problem to include a new method of calculating the solution quality. The study is also a novel application of hyper-heuristics to the movie scene scheduling problem and demonstrates one potential method for using hyper-heuristics as a solution method for the given problem. This includes the development of new low-level heuristics for the problem that are presented as well. The study showed that hyper-heuristics could be applied to the problem doing better than a random approach but that work would need to be done on improving the low-level perturbative heuristics. The study also showed that the new formulation would be tenable as a problem definition with little change to the underlying problem itself.

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Cited By

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Singh EPillay NSilva SPaquete L(2023)A Study of Ant-Based Pheromone Spaces for Generation Perturbative Hyper-HeuristicsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590367(84-92)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590367

Index Terms

Ant-Based Hyper-Heuristics for the Movie Scene Scheduling Problem
1. Computing methodologies
  1. Artificial intelligence
    1. Planning and scheduling
    2. Search methodologies
      1. Heuristic function construction
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms
    2. Online algorithms
      1. Online learning algorithms
        Scheduling algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning
        Sequential decision making

Index terms have been assigned to the content through auto-classification.

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Published In

Artificial Intelligence and Soft Computing: 20th International Conference, ICAISC 2021, Virtual Event, June 21–23, 2021, Proceedings, Part II

Jun 2021

534 pages

ISBN:978-3-030-87896-2

DOI:10.1007/978-3-030-87897-9

Editors:
Leszek Rutkowski
Czestochowa University of Technology, Częstochowa, Poland
,
Rafał Scherer
Częstochowa University of Technology, Częstochowa, Poland
,
Marcin Korytkowski
Częstochowa University of Technology, Częstochowa, Poland
,
Witold Pedrycz
Edmonton, AB, Canada
,
Ryszard Tadeusiewicz
AGH University of Science and Technology, Krakow, Poland
,
Jacek M. Zurada
Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 20 June 2021

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Singh EPillay NSilva SPaquete L(2023)A Study of Ant-Based Pheromone Spaces for Generation Perturbative Hyper-HeuristicsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590367(84-92)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590367

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Ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem

A Study of Ant-Based Pheromone Spaces for Generation Perturbative Hyper-Heuristics

A comparative study of hyper-heuristics for solving the school timetabling problem

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