The New Era of Hybridisation and Learning in Heuristic Search Design

Saïd Salhi () and Jonathan Thompson ()
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Saïd Salhi: University of Kent
Jonathan Thompson: Cardiff University

Chapter Chapter 15 in The Palgrave Handbook of Operations Research, 2022, pp 501-538 from Springer

Abstract: Abstract This chapter aims to extend on the overview of heuristic and metaheuristics described in chapter [51] by focussing on the new developments related to hybridisation and learning when designing an effective heuristic, metaheuristic, or machine learning technique. This will include a wider discussion on hybridisation, deep learning, and a brief overview of machine learning and big data. Some of the mechanisms that enhance their implementation by turning these heuristic-based techniques into powerful, efficient, and practical optimisation/statistical tools are discussed. This is attributed to the incorporation of speed-up mechanisms that can be inspired from data structure, neighbourhood reduction, cost function approximation, and parallelisation among others. The chapter also provides a highlight of potential research avenues that can be worth exploring.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-96935-6_15

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DOI: 10.1007/978-3-030-96935-6_15

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