Explanipedia

An investigation of F-Race training strategies for cross domain optimisation with memetic algorithms Open

Düriye Betül Gümüş, Ender Özcan, Jason Atkin, John H. Drake · 2022

Natural SQL: Making SQL Easier to Infer from Natural Language Specifications Open

Yujian Gan, Xinyun Chen, Jinxia Xie, Matthew Purver, John R. Woodward , et al. · 2021

Addressing the mismatch between natural language descriptions and the corresponding SQL queries is a key challenge for text-to-SQL translation. To bridge this gap, we propose an SQL intermediate representation (IR) called Natural SQL (NatS…

Natural SQL: Making SQL Easier to Infer from Natural Language Specifications Open

Yujian Gan, Xinyun Chen, Jinxia Xie, Matthew Purver, John R. Woodward , et al. · 2021

Addressing the mismatch between natural language descriptions and the corresponding SQL queries is a key challenge for text-to-SQL translation. To bridge this gap, we propose an SQL intermediate representation (IR) called Natural SQL (NatS…

A multimodal particle swarm optimization-based approach for image segmentation Open

Taymaz Rahkar Farshi, John H. Drake, Ender Özcan · 2020

Recent advances in selection hyper-heuristics Open

John H. Drake, Ahmed Kheiri, Ender Özcan, Edmund Burke · 2019

Hyper-heuristics have emerged as a way to raise the level of generality of search techniques for computational search problems. This is in contrast to many approaches, which represent customised methods for a single problem domain or a nar…

Effective reinforcement learning based local search for the maximum k-plex problem Open

Jin Yan, John H. Drake, Una Benlic, Kun He · 2019

The maximum k-plex problem is a computationally complex problem, which emerged from graph-theoretic social network studies. This paper presents an effective hybrid local search for solving the maximum k-plex problem that combines the recen…

Counterexample-Driven Genetic Programming: Stochastic Synthesis of Provably Correct Programs Open

Krzysztof Krawiec, Iwo Błądek, Jerry Swan, John H. Drake · 2018

Genetic programming is an effective technique for inductive synthesis of programs from tests, i.e. training examples of desired input-output behavior. Programs synthesized in this way are not guaranteed to generalize beyond the training se…

Impact of the 340B Pharmacy Program on Services and Supports for Persons Served by Hemophilia Treatment Centers in the United States Open

Rebecca A. Malouin, Laurel McKernan, Ann D. Forsberg, Dunlei Cheng, John H. Drake , et al. · 2018

A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming Open

Libin Hong, John H. Drake, John R. Woodward, Ender Özcan · 2017

A choice function hyper-heuristic framework for the allocation of maintenance tasks in Danish railways Open

Shahrzad M. Pour, John H. Drake, Edmund Burke · 2017

A new signalling system in Denmark aims at ensuring fast and reliable train operations, however imposes very strict time limits on recovery plans in the event of failure. As a result, it is necessary to develop a new approach to the entire…

A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem Open

Shahrzad M. Pour, John H. Drake, Lena Secher Ejlertsen, Kourosh Marjani Rasmussen, Edmund Burke · 2017

This research has been carried out as part of the PhD research project funded by Technical University of Denmark and Banedanmark company which is responsible for the operation and maintenance of the Danish railway network. This work has be…

Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants Open

John H. Drake, Jerry Swan, Geoff Neumann, Ender Özcan · 2017

A self-adaptive Multimeme Memetic Algorithm co-evolving utility scores to control genetic operators and their parameter settings Open

Ender Özcan, John H. Drake, Cevriye Altıntaş, Shahriar Asta · 2016

Automatically Designing More General Mutation Operators of Evolutionary Programming for Groups of Function Classes Using a Hyper-Heuristic Open

Libin Hong, John H. Drake, John R. Woodward, Ender Özcan · 2016

In this study we use Genetic Programming (GP) as an offline hyper-heuristic to evolve a mutation operator for Evolutionary Programming. This is done using the Gaussian and uniform distributions as the terminal set, and arithmetic operators…

A modified choice function hyper-heuristic controlling unary and binary operators Open

John H. Drake, Ender Özcan, Edmund Burke · 2015

Hyper-heuristics are a class of high-level search methodologies which operate on a search space of low-level heuristics or components, rather than on solutions directly. Traditional iterative selection hyper-heuristics rely on two key comp…

A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex Open

John H. Drake, Ender Özcan, Edmund Burke · 2015

Hyper-heuristics are search methodologies which operate at a higher level of abstraction than traditional search and optimisation techniques. Rather than operating on a search space of solutions directly, a hyper-heuristic searches a space…

Comments on: An overview of curriculum-based course timetabling Open

Edmund Burke, John H. Drake, Barry McCollum, Ender Özcan · 2015

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem Open

John H. Drake, Ender Özcan, Edmund Burke · 2015

Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and appli…

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