Automated design of efficient optimisation algorithms using Conditional Markov Chain Search

2 February 2018, 12:00 - 14:00
Chelmsford campus

ARITI is delighted to welcome Dr Daniel Karapetyan from the University of Essex.

Prof Karapetyan's presentation followed by a Q&A session will take place 12-1pm. Lunch and networking will take place 1-2pm.


Much of the automated decision support relies on our ability to solve discrete optimisation problems. Due to the diversity of applications and, as a result, the diversity of optimisation problems, design of optimisation algorithms is a labour-intensive and time-consuming work requiring expensive human expertise. We will discuss a recent framework, called Conditional Markov Chain Search (CMCS), proposed to enable automated design of heuristic optimisation algorithms. We will show that CMCS is flexible enough to model several standard metaheuristics yet its behaviour is completely parameter-controlled. We will discuss questions related to generation of efficient CMCS configurations and show that our approach has already outperformed the state-of-the-art human-designed methods on two optimisation problems.

We will assume that the audience is familiar with the concept of discrete optimisation.


Dr Daniel Karapetyan is a transitional research fellow at the Institute for Analytics and Data Science and School (IADS) of Computer Science and Electronic Engineering (CSEE), University of Essex. He received his PhD at Royal Holloway, University of London in 2010 and then worked at Simon Fraser University, Canada and University of Nottingham before joining University of Essex. Daniel's main expertise is algorithm design for decision support; he participated in many applied operational research projects with large businesses, working on ferry scheduling, airport ground operations, satellite mission planning and others. His main research interests include combinatorial optimisation, automation of algorithm design, application of data science in optimisation algorithms, heuristic methods, multi-objective optimisation, and efficient algorithm implementations.

Event Details

2 February 2018, 12:00 - 14:00
Chelmsford campus
Free to attend - lunch is provided

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