Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the
goal of automating the design of heuristic methods to solve hard computational search …

The deployment problem (DP) of a wireless sensor network (WSN) is no doubt a critical
issue because the strategies it takes will not only strongly impact the overall performance but …

Hyper-heuristics comprise a set of approaches that aim to automate the development of
computational search methodologies. This chapter overviews previous categorisations of …

The current state of the art in hyper-heuristic research comprises a set of approaches that
share the common goal of automating the design and adaptation of heuristic methods to …

This paper proposes an integrated scheduling optimization model based on mixed integer
programming to analytically characterize the U-shaped automated container terminal layout …

In recent years, deep reinforcement learning has shown great potential in solving computer
games with sequential decision-making scenarios. Hyper-heuristic is a generic search …

Abstract The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which
has initially been proposed to solve optimisation of mathematical test functions with a unique …

Hyper-heuristic is a class of methodologies which automates the process of selecting or
generating a set of heuristics to solve various optimization problems. A traditional hyper …

Hyper-heuristics can be identified as methodologies that search the space generated by a
finite set of low level heuristics for solving search problems. An iterative hyper-heuristic …

In this paper we show how tree decomposition can be applied to reasoning with first-order
and propositional logic theories. Our motivation is two-fold. First, we are concerned with how …