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.

Traversing digital learning landscapes: an Institutional and faculty case study.

Within the UK, there is a growing awareness to better understand what online educational technologies can offer in relation to learning and teaching, and how social technologies are changing communication and collaboration out with formal education. The concept of the ‘digital university’ is being widely debated within the UK Higher education sector (McCluskey and Winter, 2012), becoming embedded in educational policy, and beginning to be explored within many institutions. This session will report on one such institutional initiative, undertaken at Edinburgh Napier University in Scotland. A Digital Futures Working Group was established to: benchmark best practice in key areas including digitally enhanced education and digital literacies development; identify areas for short term action; and to produce a robust ‘digital agenda’ to inform the future direction of the university. Pivotal to this was the recognition to evolve staff digital pedagogical practices and to harness emerging digital opportunities, meet learner expectations, and meet wider expectations for contemporary able citizens. This session will be delivered in two parts. Firstly we will provide an insight into the focus of the project and the rich picture methodology used to consult with staff and students. Secondly we will specify the outcomes produced, and provide a case study of how the Faculty of Health, Life and Social Sciences engaged with the process and the progression of their digitally enabled educational practices.

An analysis of manufacturing simulation software.

As a management tool Similation Software deserves greater analysis from both an academic and industrial viewpoint. A comparative study of three packages was carried out from a 'first time' use approach. This allowed the ease of use and package features to be assessed using a simple theoretical benchmark manufacturing process. To back the use of these packages an objective survey on simulation use and package features was carried out within the manufacturing industry.This identified the use of simulation software, its' applicability and preception of user requirements thereby proposing an ideal package.

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.