On Clonal Selection.

Clonal selection has been a dominant theme in many immune-inspired algorithms applied to machine learning and optimisation. We examine existing clonal selections algorithms for learning from a theoertical and empirical perspective and assert that the widely accepted computational interpretation of clonal selection is compromised both algorithmically andbiologically. We suggest a more capable abstraction of the clonal selection principle grounded in probabilistic estimation and approximation and demonstrate how it addresses some of the shortcomings in existing algorithms. We further show that by recasting black-box optimisation as a learning problem, the same abstraction may be re-employed; thereby taking steps toward unifying the clonal selection principle and distinguishing it from natural selection.

Industrial relations in the privatised coal industry: continuity, change and contradictions.

This study seeks both to describe and account for the patterns of industrial relations which have emerged in the UK coal industry since privatisation in 1994. In doing so, it also aims to address some of the wider questions concerning the relationship between ownership and industrial relations. A series of hypotheses are advanced concerning how changes in ownership might affect industrial relations within the industry, and whether such changes would have positive or negative implications for organised labour. A case study approach is utilised to analyse labour relations developments at a number of collieries, and it is shown that the industrial relations strategies adopted by management within the new coal enterprises have had a determining effect upon the patterns of labour relations within the privati sed industry. This study also demonstrates that the emergent pattern of labour relations in the privatised industry is characterised by both continuity and change. However, whilst continuity with the patterns of labour relations established during the final decade of public ownership is shown to have had negative implications for organised labour within the industry, the changes associated with privatisation are demonstrated to have been a more ambivalent force. Change has, in different contexts, had some positive implications for organised labour, but in the majority of cases, the implications for labour have been negative. Overall, therefore, this study concludes that privatisation has had a significant influence upon industrial relations within the coal industry, and that organised labour has been detrimentally affected by these developments.

Roll Project Bin Packing Benchmark Problems.

This document describes two sets of Benchmark Problem Instances for the One Dimensional Bin Packing Problem. The problem instances are supplied as compressed (zipped) SQLITE database files.

Roll Project Job Shop scheduling benchmark problems.

This document describes two sets of benchmark problem instances for the job shop scheduling problem. Each set of instances is supplied as a compressed (zipped) archive containing a single CSV file for each problem instance using the format described in http://rollproject.org/jssp/jsspGen.pdf

Roll Project Rich Vehicle Routing benchmark problems.

This document describes a large set of Benchmark Problem Instances for the Rich Vehicle Routing Problem. All files are supplied as a single compressed (zipped) archive containing the instances, in XML format, an Object-Oriented Model supplied in XSD format, documentation and an XML parser written in Java to ease use.

A hyper-heuristic ensemble method for static job-shop scheduling.

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyperheuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.