Current state-of-the-art methodologies are mostly developed for stationary optimization problems. However, many real world problems are dynamic in nature, where dierent types of changes may occur over time. Population based approaches, such as evolutionary algorithms are frequently used in dynamic environments. Selection hyper-heuristics are highly adaptive search methodologies that aim to rais...

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived...

In project scheduling studies, to the best of our knowledge, hyper-heuristic collaborative is first-time applied with random activity durations. A based ensemble genetic programming (HH-EGP) method proposed for solving stochastic resource constrained problem (SRCPSP) by evolving an priority rules (PRs). The approach features (1) integrating critical path into resource-based policy class generat...

We propose and compare three novel heuristics for the calculation of the optimal cell radius in mobile networks based on Wideband Code Division Multiple Access (WCDMA) technology. The proposed heuristics solve the problem of the load assignment and cellular radius calculation. We have tested our approaches with experiments in multiservices scenarios showing that the proposed heuristics maximize...

University timetabling problems can be classified into two main categories: course and examination timetabling. We discuss the problem statements and constraints for each of them and provide an overview of some recent research advances that have been made by the authors and members of their research team. We particularly concentrate upon: • Meta-heuristic approaches that are less dependent upon...

A large body of knowledge has been evolving to guide efforts in how we adapt climate change. This is underpinned by a set standardised rules thumb (heuristics) that define what adaptation and it means. For example, widely accepted local issue best achieved urgent anticipatory action using participatory processes. Yet, the validity relevance these heuristics have rarely tested or questioned. If ...

The primary goal of the research reported in this thesis is to identify what criteria are responsible for the good performance of a heuristic rule evaluation function in a greedy top-down covering algorithm both in classification and regression. We first argue that search heuristics for inductive rule learning algorithms typically trade off consistency and coverage, and we investigate this trad...

This paper studies the impact of demand-prioritization on Space-Division Multiplexing Elastic Optical Networks (SDM-EON). For this purpose, we solve static Routing, Modulation Level, Spatial Mode, and Spectrum Assignment (RMLSSA) problem using 34 different explainable strategies. Although previous works have applied heuristics or meta-heuristics to perform demand-prioritization, they not focuse...

In this paper, we present an investigation into using fuzzy methodologies to guide the construction of high quality feasible examination timetabling solutions. The provision of automated solutions to the examination timetabling problem is achieved through a combination of construction and improvement. The enhancement of solutions through the use of techniques such as metaheuristics is, in some ...