Unsupervised land-use/cover classification is of great interest, since it becomes even more difficult to obtain high-quality labeled data. Still considered one of the most used clustering techniques, the well-known k-means ...

Abstract: In this article we build multi-objective hyperheuristics (MOHHs) using the multi-objective evolutionary algorithm NSGA-II for solving irregular 2D cutting stock problems under a bi-objective minimization schema, ...

An innovative optimization strategy by means of hyper-heuristics is proposed. It consists of a parallel combination of three metaheuristics. In view of the need both to escape from local optima and to achieve high diversity, ...

This paper presents the general framework of a parallel cooperative hyper-heuristic optimizer (PCHO) to solve systems of nonlinear algebraic equations with equality and inequality constraints. The algorithm comprises the ...

A hyperheuristic optimization technique to reduce computational times for the design of pipeline networks is presented. The proposed strategy is an A-team approach comprising the guided execution of three metaheuristics: ...

This document describes a feasible way of implementing hyper-heuristics into self-driving cars for decision-making. Hyper-heuristics techniques are used as an automated procedure for selecting or generating among a set of ...

In this paper we introduce a hyperheuristic to solve hard strip packing problems. The hyperheuristic manages a sequence of greedy low-level heuristics, each element of the sequence placing a given number of objects. A ...