Uncertainty-Aware Planning and Scheduling in the Process Industries
Lead Research Organisation:
Imperial College London
Department Name: Computing
Abstract
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Publications
Diangelakis N
(2015)
Decentralized Multiparametric Model Predictive Control for Domestic Combined Heat and Power Systems
in Industrial & Engineering Chemistry Research
Menke R
(2015)
Approximation of System Components for Pump Scheduling Optimisation
in Procedia Engineering
Wright R
(2015)
Experimental Investigation of Resilience and Pressure Management in Water Distribution Networks
in Procedia Engineering
Wright R
(2015)
Optimized Control of Pressure Reducing Valves in Water Distribution Networks with Dynamic Topology
in Procedia Engineering
Hanasusanto G
(2015)
K -Adaptability in Two-Stage Robust Binary Programming
in Operations Research
Wright R
(2015)
Hydraulic Resilience Index for the Critical Link Analysis of Multi-feed Water Distribution Networks
in Procedia Engineering
Hanasusanto G
(2015)
A comment on "computational complexity of stochastic programming problems"
in Mathematical Programming
Wright R
(2015)
Control of water distribution networks with dynamic DMA topology using strictly feasible sequential convex programming WATER DISTRIBTUION NETWORKS WITH DYNAMIC TOPOLOGY
in Water Resources Research
Luong D
(2016)
A Weighted Mirror Descent Algorithm for Nonsmooth Convex Optimization Problem
in Journal of Optimization Theory and Applications
| Description | We investigate decision making under uncertainty, i.e. the ubiquitous process of selecting a course of action in order to solve a problem with incomplete information. For example, in industrial systems, meeting customer demands requires planning a production schedule which is robust to machine failures and unreliable customers. Mathematical optimisation provides powerful methods computing such schedules. We focus on re-optimization techniques which repair inefficiencies determined when unknown information is revealed. The benefit of this approach has been demonstrated in various settings, e.g. public and product transportation. We show that re-optimization does not always help to overcome well-known theoretical computation obstacles in scheduling problems. However, if the initial planning is designed using lexicographic optimization, we show significant benefit. Lexicographic optimal solutions have nice structure in the spirit of the well-structured alphabetical order of dictionaries. Furthermore, in analogous way that a damaged dictionary remains a useful piece of knowledge, lexicographic optimization allows efficient re-optimisation under uncertainty. This work formalises, quantifies and proves mathematically these ideas. Furthermore, it develops a novel lexicographic optimisation method with a performance comparable to using powerful commercial software. Exploiting sparsity with specialized Semidefinite Programming (SDP) relaxations had a huge impact on the application of SDP relaxations to realistic polynomial optimization problems. Indeed, when using the classical Lasserre hierarchy, it is only possible to solve problems with a few dimensions, but by exploiting the sparsity present in many applications, it is possible to solve problems with several hundred variables. In our research we argued that many applications have additional structure that can be exploited to similar effect. In particular, many large scale polynomial optimization problems have their origins from the discretization of an infinite dimensional model. The resulting finite dimensional model is sparse but has a large number of degrees of freedom. Optimization models that fit this class are boundary value problems, optimization with PDEs , optimal control, and Markov Decision Processes, among others.Despite the progress made in the last decade, it is still not possible to solve realistic instances of the models arising in these applications using sparse SDP relaxations. The main contribution of this work was to show how to take advantage of both the sparse and hierarchical structure present in many applications. Our theoretical results suggest that under appropriate conditions we should expect significant improvements in computational complexity. Our numerical results further support this claim, and we showed that a multigrid approach can improve the robustness and reduce the time required to solve large scale polynomial optimization problems. |
| Exploitation Route | An interesting feature of our approach is its applicability to other problems arising in network communications and facility location. The polynomial optimisation problems and sum-of-squres application also have many applications in data science. |
| Sectors | Chemicals,Digital/Communication/Information Technologies (including Software),Energy,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
| URL | http://wp.doc.ic.ac.uk/rmisener/,www.doc.ic.ac.uk/~pp500,http://wp.doc.ic.ac.uk/wwiesema/ |
| Description | Our finding that lexicographic ordering helps recover better feasible solutions after an initial perturbation has been of significant interest to the Royal Mail Data Science Group. In collaboration with Royal Mail, we are now working to translate the research into practice. |
| First Year Of Impact | 2017 |
| Sector | Digital/Communication/Information Technologies (including Software),Energy,Environment,Transport |
| Impact Types | Societal,Economic,Policy & public services |
| Description | BASF Research Project |
| Amount | € 50,000 (EUR) |
| Organisation | BASF |
| Sector | Private |
| Country | Germany |
| Start | 05/2017 |
| End | 08/2017 |
| Description | Early Career Fellowship in Software development for novel engineering research |
| Amount | £984,063 (GBP) |
| Funding ID | EP/P016871/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2017 |
| End | 08/2022 |
| Description | Grand Challenges Research Fund |
| Amount | £1,515,900 (GBP) |
| Funding ID | EP/P029558/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 05/2017 |
| End | 04/2020 |
| Description | Industrial CASE Account - Imperial College London 2017 |
| Amount | £1,499,328 (GBP) |
| Funding ID | EP/R511961/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2017 |
| End | 09/2022 |
| Description | Industrial CASE studentship with Schlumberger |
| Amount | £27,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2017 |
| End | 09/2020 |
| Description | BASF - Statistics and Machine Learning for Chemicals |
| Organisation | BASF |
| Country | Germany |
| Sector | Private |
| PI Contribution | Using a problem relevant to BASF, my team investigates a large-scale industrially-relevant optimisation problem that includes machine-learning tree-based models in the objective function. Our methodology leverages decomposition structure in the optimisation problem. Our work directly impacts BASF's energy efficiency and is easily extended to other applications, e.g. materials design and finance, since tree-based models are well suited for modelling unknown nonlinear functions. Furthermore, our optimisation problem may broadly incorporate other machine-learning models, contributing to the design of a unifying framework where mathematical optimisation is integrated with machine-learning and data analytics for effective decision making. My team contributed the expertise and developed the methodology. |
| Collaborator Contribution | BASF finds machine-learning tree-based models effective for modelling catalyst behaviour because closed-form mathematical expressions are not known for many chemical catalysis applications. Catalysts are essential for energy efficiency at BASF. Therefore, developing the best-performing catalysts requires optimising over their tree-based models. BASF proposed a large-scale industrially-relevant optimisation problem that contains machine-learning tree-based models in the objective function. The optimisation problem considers the tree-based models but also penalises solutions that are far from training data, i.e. it optimises the tree-based models closer to the experimental data. BASF contributed £40k in initial seed funding to fund my PhD student associated with this project. |
| Impact | Based on the outcomes of this project, BASF has now funded a full PhD scholarship (£270k, 2019 - 2023). This PhD student is associated with the EPSRC projects and partially trained by researchers associated with the EPSRC projects. BASF is also funding (starting 2020) £110k (cash) towards the PhD of Jose Folch. Starting 2023, BASF will fund another PhD student (contributing £115k cash). BASF also supported my successful BASF / RAEng Research Chair in Data-Driven Optimisation. PhD student Miten Mistry (paid by BASF) collaborated with PDRA Dimitris Letsios and PI Ruth Misener to develop a submission to the 2019 STEM for Britain competition. Miten's accomplishment is documented here: http://www.imperial.ac.uk/news/190330/department-computing-researchers-selected-present-research/ Our joint paper with the BASF team has been accepted to INFORMS Journal on Computing (https://arxiv.org/abs/1803.00952). We also have a number of NeurIPS publications, e.g. as documented here https://www.imperial.ac.uk/news/241071/machine-learning-techniques-from-imperial-basf/ |
| Start Year | 2017 |
| Description | Collaboration with the research group of Processor Liesbet Geris |
| Organisation | University of Liege |
| Country | Belgium |
| Sector | Academic/University |
| PI Contribution | We provided the expertise in optimisation under uncertainty. |
| Collaborator Contribution | The group of Professor Liesbet Geris provided the application and the computing resources. PhD student Mohammad Mehrian visited the group of Ruth Misener to collaborate on this project. PhD student Simon Olofsson (not funded by the EPSRC, but Simon's training leads him to collaborate on the project) also visited the group of Professor Geris. |
| Impact | We have published two full-length journal papers with Professor Geris' group: one is in Biotechnology & Bioengineering (2018) and the other is in IEEE Transactions on Biomedical Engineering (2019). We have also published several conference papers together. |
| Start Year | 2016 |
| Description | Royal Mail Data Science Group |
| Organisation | Royal Mail plc |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | The Royal Mail wants to minimise the number of vans required at each of their "Delivery Offices" or DOs. Royal Mail has approximately 1250 Delivery Offices and 43k vans, so reducing the number of vans is a big cost (and environmental) savings for the company. My research team has developed a methodology for responding quickly to uncertainty. In our work, we design a schedule the night before based on historical data. Then, when anything goes wrong on the day, our recovery strategy quickly adapts to the change. We show that optimising the night-before schedule in a good way, i.e. with lexicographic optimisation, helps recovery on the day itself. Moreover, our results make Royal Mail more comfortable that they can reduce the number of vans without penalty. |
| Collaborator Contribution | Our collaborators in the Royal Mail Data Science Group have meet with us for ~5 full days over the course of the last 6 months. Our collaborators also have provided us with test sets to try out our ideas. |
| Impact | Royal Mail has offered to fund an EPSRC CDT PhD studentship for further collaborations. Royal Mail has also offered to write a letter supporting one of the REF Impact Case studies. MSc student Natasha Page, who collaborated with Royal Mail and EPSRC-funded researchers, was honoured for excellence in her MSc thesis by the Operational Research Society. Natasha was awarded "Runner-Up" to the 2019 May Hicks Award (https://www.theorsociety.com/what-we-do/awards-medals-and-scholarships/may-hicks-award/). The associated Imperial News Article explicitly credits the EPSRC funding (https://www.imperial.ac.uk/news/191227/department-computing-msc-student-honoured-joint/). MEng student Suraj G, who also collaborated with Royal Mail and the EPSRC-funded researchers, was honoured for excellence in his MEng thesis by the Imperial Department of Computing as one of the best theses in his year. Suraj won the "NewVoice Media Prize for Computing". The initial work with Royal Mail was accepted by the conference COCOA 2019 (http://cocoaconference.org/program.html, https://link.springer.com/chapter/10.1007/978-3-030-36412-0_6). The initial conference paper incorporates the work of Royal Mail, the EPSRC-funded researchers, and MSc student Natasha Page. We have also submitted a full length journal version of the work (preprint: https://arxiv.org/abs/1912.06862). The full length version additionally incorporates the work of MEng student Suraj G. |
| Start Year | 2018 |
| Description | Decision-making under uncertainty |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | Imperial Enterprise developed a long-form read about my group and the other groups at Imperial working on decision-making under uncertainty (https://www.imperial.ac.uk/stories/decision-making/). Then we held an online event (148 people in attendance) to talk more about decision-making under uncertainty (http://www.imperial.ac.uk/enterprise/business/partners/ibp-events/decision-making-under-uncertainty-february-2021/). |
| Year(s) Of Engagement Activity | 2021 |
| URL | http://www.imperial.ac.uk/enterprise/business/partners/ibp-events/decision-making-under-uncertainty-... |
| Description | GitHub page |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | We make our EPSRC-funded software contributions available open source on our group's GitHub page (https://github.com/cog-imperial). This allows practitioners and other researchers to use our ideas. Our most popular code (OMLT) has 15k downloads a month. Several other codes supported by this grant are also getting a lot of use. |
| Year(s) Of Engagement Activity | 2020,2021,2022,2023 |
| URL | https://github.com/cog-imperial |
| Description | Interview for a film about the Royal Academy of Engineering |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | I appeared in a Royal Academy of Engineering video discussing my research. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.youtube.com/watch?v=2gYp1nm6D3M |
| Description | Keynote at the 2018 European Symposium for Computer-Aided Process Engineering |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | I will be giving a keynote at the 2018 European Symposium for Computer-Aided Process Engineering. This is my user community, i.e., the community of engineers who would be best suited to take the contributions to mathematical optimisation and computer science that my team has made and translate them widely into practice. I will be using the keynote (in June 2018) to discuss the outcomes of two EPSRC grants. I already know that the community is keenly interested in our research, but I hope to really fan the flames and get everyone on board with trying our new mathematical approaches. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://www.tugraz.at/events/escape28/scientific-program/keynote-speakers/ |
| Description | Seminar at Carnegie Mellon |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | 80 postgraduate students and their supervisors attended a seminar given by Ruth Misener, which led to discussions on the topic and interest in future research |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://twitter.com/crislopeslara/status/1102990243752542208 |
| Description | Twitter feed |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | My group developed a Twitter feed (https://twitter.com/CogImperial) that presents our work to the community. We have 1,134 Twitter followers. On this Twitter feed, we publicize and discuss our research. In addition to our papers, we also make available on our Twitter feed the videos that appear on our YouTube channel (https://www.youtube.com/c/CogImperial/featured) and the open source software that appears on our GitHub page (https://github.com/cog-imperial). |
| Year(s) Of Engagement Activity | 2021,2022 |
| URL | https://twitter.com/CogImperial |
| Description | Voice of the Future 2016 |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Attending the 2016 "Voice of the Future". The event gives the opportunity for younger representatives of a wide range of science and engineering organisations to ask questions of leading figures dealing with science in Parliament and Government, such as MPs, Ministers, and scientific advisers - with the event chaired by a member of the House of Commons Science and Technology Select Committee. The event has been a huge success in previous years - last March's Voice of the Future was broadcast on BBC Parliament. |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.rsb.org.uk/policy/policy-events/voice-of-the-future |
| Description | YouTube channel |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | With the advent of online conferences, my group has had to record a lot of videos about our research work. After we present these videos at conference, we make them available to the general public on our group's YouTube channel (https://www.youtube.com/channel/UCXRdjQRm9XfZj2c4XW1xpzg). These videos became so popular that we now make videos independently of conferences. Even if a conference is in person and we're not going to be recorded, we still make a YouTube video. We also hosted a conference using our YouTube channel. So far, our YouTube channel has >10k views and 308 subscribers. |
| Year(s) Of Engagement Activity | 2020,2021,2022,2023 |
| URL | https://www.youtube.com/c/CogImperial/featured |