| An effective PSO-inspired algorithm for the team orienteering problem DC Dang, RN Guibadj, A Moukrim European Journal of Operational Research 229 (2), 332-344, 2013 | 109 | 2013 |
| A memetic algorithm for the team orienteering problem H Bouly, DC Dang, A Moukrim 4or 8 (1), 49-70, 2010 | 82 | 2010 |
| Level-based analysis of genetic algorithms and other search processes D Corus, DC Dang, AV Eremeev, PK Lehre IEEE Transactions on Evolutionary Computation 22 (5), 707-719, 2017 | 56 | 2017 |
| Self-adaptation of mutation rates in non-elitist populations DC Dang, PK Lehre International Conference on Parallel Problem Solving from Nature, 803-813, 2016 | 54 | 2016 |
| Escaping local optima using crossover with emergent diversity DC Dang, T Friedrich, T Kötzing, MS Krejca, PK Lehre, PS Oliveto, ... IEEE Transactions on Evolutionary Computation 22 (3), 484-497, 2017 | 53 | 2017 |
| Level-based analysis of genetic algorithms and other search processes D Corus, DC Dang, AV Eremeev, PK Lehre International Conference on Parallel Problem Solving from Nature, 912-921, 2014 | 48 | 2014 |
| A branch-and-cut algorithm for solving the team orienteering problem DC Dang, R El-Hajj, A Moukrim International Conference on AI and OR Techniques in Constriant Programming …, 2013 | 48 | 2013 |
| Heuristic solutions for the vehicle routing problem with time windows and synchronized visits S Afifi, DC Dang, A Moukrim Optimization Letters 10 (3), 511-525, 2016 | 44 | 2016 |
| A pso-based memetic algorithm for the team orienteering problem DC Dang, RN Guibadj, A Moukrim European Conference on the Applications of Evolutionary Computation, 471-480, 2011 | 39 | 2011 |
| Solving the team orienteering problem with cutting planes R El-Hajj, DC Dang, A Moukrim Computers & Operations Research 74, 21-30, 2016 | 38 | 2016 |
| Runtime analysis of non-elitist populations: From classical optimisation to partial information DC Dang, PK Lehre Algorithmica 75 (3), 428-461, 2016 | 38 | 2016 |
| A simulated annealing algorithm for the vehicle routing problem with time windows and synchronization constraints S Afifi, DC Dang, A Moukrim International Conference on Learning and Intelligent Optimization, 259-265, 2013 | 36 | 2013 |
| Efficient optimisation of noisy fitness functions with population-based evolutionary algorithms DC Dang, PK Lehre Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms …, 2015 | 34 | 2015 |
| Simplified runtime analysis of estimation of distribution algorithms DC Dang, PK Lehre Proceedings of the 2015 Annual Conference on Genetic and Evolutionary …, 2015 | 33 | 2015 |
| Escaping local optima with diversity mechanisms and crossover DC Dang, T Friedrich, T Kötzing, MS Krejca, PK Lehre, PS Oliveto, ... Proceedings of the Genetic and Evolutionary Computation Conference 2016, 645-652, 2016 | 32 | 2016 |
| Toward a unifying framework for evolutionary processes T Paixăo, G Badkobeh, N Barton, D Çörüş, DC Dang, T Friedrich, ... Journal of Theoretical Biology 383, 28-43, 2015 | 24 | 2015 |
| Emergence of diversity and its benefits for crossover in genetic algorithms DC Dang, T Friedrich, T Kötzing, MS Krejca, PK Lehre, PS Oliveto, ... International Conference on Parallel Problem Solving from Nature, 890-900, 2016 | 23 | 2016 |
| Populations can be essential in tracking dynamic optima DC Dang, T Jansen, PK Lehre Algorithmica 78 (2), 660-680, 2017 | 20 | 2017 |
| Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels DC Dang, PK Lehre Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 18 | 2014 |
| Evolution under partial information DC Dang, PK Lehre Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 13 | 2014 |
Per Kristian LehreUniversity of BirminghamVerified email at cs.bham.ac.uk
