This paper introduces a new and very simple search methodology called Late Acceptance
Hill-Climbing (LAHC). It is a local search algorithm, which accepts non-improving moves …

Simulated Annealing (SA) is one of the oldest metaheuristics and has been adapted to solve
many combinatorial optimization problems. Over the years, many authors have proposed …

Adaptive large neighborhood search (ALNS) is a useful framework for solving difficult
combinatorial optimisation problems. As a metaheuristic, it consists of some components …

Machine learning has been expansively examined with data classification as the most
popularly researched subject. The accurateness of prediction is impacted by the data …

A selection hyper-heuristic is a high level search methodology which operates over a fixed
set of low level heuristics. During the iterative search process, a heuristic is selected and …

This work addresses the unrelated parallel machine scheduling problem with sequence‐
dependent setup times, in which a set of jobs must be scheduled for execution by one of the …

This article tackles a patient admission scheduling using Late Acceptance Hill Climbing
Algorithm (LAHC). The LAHC algorithm is among the newly proposed metaheuristic-based …

In this chapter we will focus on models and algorithms for creating fair course timetables. For
this purpose we consider the distribution of the timetable quality over the stakeholders. We …

The artificial bee colony (ABC) is a population-based metaheuristic that mimics the foraging
behaviour of honeybees in order to produce high-quality solutions for optimisation problems …

This paper presents a new single-parameter local search heuristic named step counting hill
climbing algorithm (SCHC). It is a very simple method in which the current cost serves as an …