BGIAO 2013 - International Workshop on Bridging the Gap between Industry and Academia in Optimisation
Topics/Call fo Papers
Meta-heuristic optimisation techniques have been widely applied to solving many practical problems arising in industrial domains, with much success reported in the literature. However, there remains a worrying void between scientific research into optimisation techniques and those problems faced by end-users and addressed by commercial optimisation software vendors. From a commercial perspective, the problems addressed by academia are often too simplistic compared to those faced in the real-world, failing to embrace many real-world constraints (For example, even ‘rich-vehicle routing’ research fails to address concerns of customers regarding non-trivial loading problems, working-time legislation, rush-hour speed modelling and asymmetric distance networks). From the scientific perspective, there is a lack of advanced meta-heuristic techniques apparent in commercial software, that has been attributed in part to the academic community failing to demonstrate that their solutions are applicable to the needs of the commercial world, and in part to academics failing to impart their message the industrial community.
This workshop aims to address the gap between current state-of-the art optimization techniques emerging in the academic literature and the real concerns of those in industry who would like to use the techniques by providing an opportunity for researchers to discuss:
Development of new benchmark sets of data that include relevant real-world constraints to demonstrate relevance of academic techniques.
Metrics by which problems should be evaluated relevant to practitioners.
Methods for comparing algorithms that address concerns of practitioners.
Discussion of real-world problem constraints.
Papers are likely (but not limited to) to address one of the following :
Generation of new problems
Creation of standards and metrics for evaluating and comparing algorithms
Frameworks for comparing algorithms.
Real-world constraints in a variety of domains.
Practical applications of optimization algorithms
Workshop Chairs
Prof Emma Hart is an experienced researcher in the area of optmisation and hyper-heuristics, being one of the original authors of the term’hyper-heuristics’ in the early 2000s. She has published widely on the use of evolutionary algorithms applied to scheduling and timetabling problems, as well as in hyper-heuristics applied to a variety of domains. She is currently the holder of a large national research grant, investigating the use of hyper-heuristics that continuously learn and improve over time, which has collaborators from the logistics and forestry industry.
Kevin Sim is a researcher who works in the field of hyper-heuristics and problem-classification algorithms, and works with Prof. Hart on a large national grant on hyper-heuristics. He is also co-chair of a workshop at Evo-Star 2013 called EvoIndustry.
This workshop aims to address the gap between current state-of-the art optimization techniques emerging in the academic literature and the real concerns of those in industry who would like to use the techniques by providing an opportunity for researchers to discuss:
Development of new benchmark sets of data that include relevant real-world constraints to demonstrate relevance of academic techniques.
Metrics by which problems should be evaluated relevant to practitioners.
Methods for comparing algorithms that address concerns of practitioners.
Discussion of real-world problem constraints.
Papers are likely (but not limited to) to address one of the following :
Generation of new problems
Creation of standards and metrics for evaluating and comparing algorithms
Frameworks for comparing algorithms.
Real-world constraints in a variety of domains.
Practical applications of optimization algorithms
Workshop Chairs
Prof Emma Hart is an experienced researcher in the area of optmisation and hyper-heuristics, being one of the original authors of the term’hyper-heuristics’ in the early 2000s. She has published widely on the use of evolutionary algorithms applied to scheduling and timetabling problems, as well as in hyper-heuristics applied to a variety of domains. She is currently the holder of a large national research grant, investigating the use of hyper-heuristics that continuously learn and improve over time, which has collaborators from the logistics and forestry industry.
Kevin Sim is a researcher who works in the field of hyper-heuristics and problem-classification algorithms, and works with Prof. Hart on a large national grant on hyper-heuristics. He is also co-chair of a workshop at Evo-Star 2013 called EvoIndustry.
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Last modified: 2013-01-19 15:21:20