Automated Scheduling Optimisation and Planning (ASAP) Research Group
  • Print

 Current Projects

Project TitleInvestigatorsFunding SourceAmount AwardedStart DateEnd Date

Encouraging Lifelong Learning for an Inclusive and Vibrant Europe                                        

Assoc Prof  Rong Qu (PI)          

Prof Robert John (CI)

Assoc Prof Jason Atkin (CI)

European Commission- Horizon 2020 £392,000 01/10/2016 30/09/2019

The ENLIVEN (Encouraging Lifelong Learning for an Inclusive and Vibrant Europe) project is funded by the European Commission.  This is a project within a consortium of 10 European countries.  At the Automated Scheduling Planning and Optimisation (ASAP) Research Group, the School of Computer Science , the project focuses on knowledge discovery, based on analysing large databases collected from the consortium member countries, to establish knowledge bases within case based reasoning systems for policy making in lifelong learning in Europe.  The objectives include to mine knowledge from large amount of data, and to develop intelligent decision support systems to support policy makers throughout the policy making process for adult lifelong learning.


DEAS: EPSRC Digital Economy: Digitally Enhanced Advanced Services (DEAS) NetworkPlus

University of Exeter (PI)

Prof Robert John (PI)   

Aston University (CI)

Cranfield University (CI)

University of Greenwich (CI)                         




Digitally Enhanced Advanced Services (DEAS) offer enormous potential for value creation enabled by transformative digital technologies. Here the focus of the firm is on delivering ‘capability’, rather than on conventional sale of product or service, and so value delivered through how the product or service is used. This is a major change in how firms earn money (e.g.: payment-per-use, availability or outcome) and is an area where the UK has the potential to excel.

 This Digital Economy (DE) Network+ aims to deliver a vibrant community that will position the UK as the internationally leading research hub for DEAS. Through this programme we will:

  • foster a community which brings together both ‘Early Career’ and experienced researchers in an interdisciplinary networks panning Computer Science, Human Factors, Engineering and Business,
  • (working collaboratively on fundamental (TRLs 1-3) technological challenges (i.e.: AI techniques, data analytics, and associated technologies) across Manufacturing, Transport and Financial services,
  • with a clear ‘line of sight’ to achieve industrial impact (we bring match funding of £1.4M to demonstrate industries willingness to engage),
  • delivering a formal repository of successful DEAS use-cases to provide a platform for scale up research and practice.

Multi-objective timetabling with fairness

Assoc Prof Ender Ozcan (PI)                              Invest NI and Technology Strategy Board


01/07/17 30/06/19

This KTP project between the University of Nottingham and EventMAP will further our collaborative work in the emerging area of ‘fairness’ measures in timetabling and scheduling. In the case of higher education,  

introducing the concept of subjective ‘fairness’ into the workings of their products is an important step to improving the overall satisfaction levels of teachers, students and university staff with their day-to-day work. So, for example, those sometimes unavoidable, less-than-ideal compromises in timetables – which timetablers will know as violations of soft constraints – can be distributed in an equitable way amongst affected parties while still maintaining a maximally efficient timetable. It should go without saying that this incorporation of fairness measures into EventMAP's work will greatly increase the value that can be brought to improving student experience and staff satisfaction levels for the academic clients.

European industrial doctorate for advanced, lightweight and silent, multifunctional composite structures

Assoc Prof Dimitrios Chronopoulos (PI)

Assoc Prof Ender Ozcan (CI)

Assoc Prof  Savvas Triantafyllou (CI)

Prof Gregor Tanner(CI)

Donald Brown  (CI)

Assis Prof Andrew Parkes (CI)

European Commission (Brussels)


01/03/2018 28/02/2022

Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Despite their superior structural characteristics, composite structures exhibit poor dynamic and acoustic isolation levels compared to conventional metallic ones. As a result and in order to maintain the comfort levels in the passenger and payload compartments within acceptable limits, additional acoustic and vibrational isolation technologies (sound packages) are necessary in several transport applications. If non-optimally designed for a certain application, these sound packages can add substantial weight to the structure, compromising the weight benefits gained by the employment of composites.

The aforementioned challenges imply an urgent and genuine need for development of lightweight and multifunctional structures, for modern industrial transport applications. The N2N Training Network aims at developing a high-fidelity and efficient Multidisciplinary Design Optimization (MDO) scheme for multifunctional composites having poroelastic inclusions and combining minimum mass with maximum damping and comfort levels.

On the research side, N2N will focus on developing multiscale models for obtaining a comprehensive description of random poroelastic materials coupled to a composite structural segment. Understanding the interaction of acoustic waves with such complex materials is another scientific challenge that the Network will tackle. N2N aims at developing reliable tools for providing accurate optimal designs for multifunctional composite structures that combine lightweight properties with exceptional acoustic and vibration isolation.

On the training side, N2N will provide a fully supportive environment for 3 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multidisciplinary (industrial and academic) research environments.

OptiMACS - European industrial doctorate for efficient multidisciplinary design Optimization of Multifunctional Aerospace Composite Structures

Assoc Prof Dimitrios Chronopoulos (PI)

Assoc Prof Ender Ozcan (CI)

Prof Arthur Jones (CI)

Assoc Prof Tom Turner (CI)

Senior Research Fellow Louise Brown (CI)

European Commission (Brussels) €1.3M 01/05/2018 30/04/2022

Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Optimizing the design of aerospace composites vis-à-vis the entire range of operational constraints (i.e. reliability, stability, strength, weight, noise, manufacturability and cost) to which the aircraft structures are subject, results in a particularly challenging task for the structural designer. Despite the volume of recent work dedicated to new Multidisciplinary Design Optimization (MDO) models and techniques, the ‘No free lunch theorem in optimisation’ is constantly confirmed.

A genuine need is therefore identified for a programme that will: i) Develop, deliver and implement novel and efficient structural MDO technological tools for the European aerospace industry, ii) Nurture and train the next European generation of MDO research professionals. OptiMACS has an intersectoral character, drawing know-how from both academic and industrial research and innovation teams. It also has an intensely multi-disciplinary character, coupling expertise from mechanical, aerospace, manufacturing and software engineering, as well as from the area of applied mathematics.

On the research side, OptiMACS will focus on improving the accuracy and efficiency of the MDO platform currently employed by AIRBUS. This will be achieved by enhancing the design models and criteria related to composites failure and manufacturing, developing and implementing multiscale models for composites as well as investigating advanced MDO algorithms and architectures for enhancing efficiency.

On the training side, OptiMACS will provide a fully supportive environment for 5 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multi-disciplinary environment, spending at least 50% of their time at the premises of the industrial beneficiaries.

OPTIMISED: Operational Planning Tool Interfacing Manufacturing Integrated Simulations with Empirical Data

Prof Robert John (PI)                              European Commission- Horizon 2020


01/11/2015 31/10/2018

OPTIMISED is a 10-party, three year, EU-funded consortium project, comprising SME's, large companies and research institutions from across Europe.  The key aims of the project are contained in the full project title: Operational Planning Tool Interfacing Manfacturing Integrated Simulations with Empirical Data. 

OPTIMISED will develop and demonstrate a manufacturing scheduling optimisation system, which uses real-time smart sensors and big data analytics to monitor, react to and improve manufacturing performance.  Within the scope, the impact of energy management on factory planning and optimisation witll be speciaically addressed.

OPTIMISED will use the principles of Measure, Simulate, Optimise.

Predictive and Prescriptive Analytics with Optimisation for Business Intelligence

Assoc Prof Dario Landa-Silva (PI)

Assis Prof Isaac Triguero (CI)

Innovate UK £207,551 01/10/2016 30/06/2019

This KTP project seeks to enable PXtech to develop predictive and prescriptive analytics with optimisation capability to maintain their leading industry position as a Business Intelligence Solution provider through the application of advanced data analysis, data mining, machine learning, modelling and optimisation techniques. The project will develop techniques to predict future outcomes in order to prescribe long-term planning that aligns with the market needs. Predictive and prescriptive analytics including optimisation will help a business to discover patterns and develop new models to predict (resulting in deeper insights) and prescribe (resulting in better planning), in order to improve business performance.

Automated Intelligent Decision Support Using Hyper-Heuristics

Assis Prof Ender Ozcan (PI), Nelishia Pillay Royal Society £ 11,719 01/11/2015 31/10/2017

This grant will support a two-year long collaborative research project through exchange of visits with Prof Nelishia Pillay and a PhD student from the School of Mathematics, Statistics and Computer Science at University of KwaZulu-Natal. Intelligent decision support systems are playing an increasingly important role in providing solutions to various computational problems in society, industry, academia and government. However, the design, development and maintenance of heuristic methods underpinning those intelligent decision support systems are extremely challenging, time-consuming and so costly, often requiring human expert intervention. This collaboration aims to study adaptive, effective, generic, reusable and low-cost hyper-heuristics automating the heuristic design process for intelligent decision support, focusing on vehicle routing, packing and timetabling domains.

COSLE (Collaborative Optimisation in a Shared-Logistics Environment)

Assoc Prof Dario Landa-Silva (PI)

Prof Robert John (CI)

Innovate UK £ 299,482 01/06/2015 31/05/2017

This project (led by Microlise Ltd) is to develop an innovative service to enable collaboration in a shared freight transport logistics environment. We will bring location data (about where goods, vehicles, senders and consignees are at any time, etc.) and environmental data (weather, traffic, events, etc.) together with GPS, vehicle telematics, optimisation, image processing and mobile technology (including augmented reality). This innovative service will enable a shared distribution concept to reduce freight empty runs and create business opportunities for users at all levels.

Channel 4 Project

ASAP Team Channel 4 Under NDA 2013 Ongoing

An ASAP team is working with Channel 4 (a national TV company) in order to investigate the application of optimisation techniques to the scheduling of commercials during advertising breaks. The objective is to provide schedules that increase advertising effectiveness and lead to greater advertiser satisfaction.


System Tuning and Adaptation for the Heathrow Target Start-Up Approval Time (TSAT) Allocation System

Assis Prof Jason Atkin (PI)

Assis Prof Geert De Maere (CI)

NATS £ 227,300 15/12/2011 Ongoing

This research considers the problem of allocating pushback times to departing aircraft, specifying the time at which they will be given permission to push back from their allocated stand, start their engines, and commence their taxi to the runway. The aim of this research is to first predict the delay (defined as the waiting time at the stand or runway) for each departure, then to use this to calculate a pushback time such that an appropriate amount of the delay is absorbed at the stand, prior to starting the engines. A two-stage approach has been used, where the feasibility of the second stage (pushback time allocation) has to be considered within the first stage (takeoff sequencing). This problem: has a non-linear objective function with a non-convex component; involves the integration of two sequence dependent separation problems; and has separations that can vary over time. Algorithms to solve these problems had been developed by the ASAP research group. This project involves the ongoing research into the appropriate tuning and adaptation of these algorithms to handle the changing real world environment.

ASAP Research Group

The University of Nottingham
School of Computer Science
Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB

telephone: +44 (0) 115 8466543