Christian
Christian
 
Blum
Blum

Scientific Researcher
Scientific Researcher


Christian
Christian
 
Blum
Blum
Scientific Researcher
Scientific Researcher

Logic and Reasoning
Logic and Reasoning
(+34) 93 580 9570 ext.
214
214
christian.blum@iiia.csic.es
christian.blum@iiia.csic.es
Research areas:
  • Combinatorial Optimisation
  • Multiagent Systems
  • Learning
  • Swarn Computing
  • Bioinformatics
  • Optimisation
  • Combinatorial Optimisation
  • Multiagent Systems
  • Learning
  • Swarn Computing
  • Bioinformatics
  • Optimisation
Impact areas:
  • Smart Cities
  • Transport / Automotive
  • Smart Cities
  • Transport / Automotive
SDGs:
  • GOAL 11: Sustainable Cities and Communities
  • GOAL 11: Sustainable Cities and Communities
2021
Christian Blum,  & Gabriela Ochoa (2021). A comparative analysis of two matheuristics by means of merged local optima networks. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2020.08.008. [BibTeX]
Filippo Bistaffa,  Christian Blum,  Jesús Cerquides,  Alessandro Farinelli,  & Juan A. Rodríguez-Aguilar (2021). A Computational Approach to Quantify the Benefits of Ridesharing for Policy Makers and Travellers. IEEE Transactions on Intelligent Transportation Systems, 22, 119-130. https://doi.org/10.1109/TITS.2019.2954982. [BibTeX]  [PDF]
Teddy Nurcahyadi,  & Christian Blum (2021). Adding Negative Learning to Ant Colony Optimization:A Comprehensive Study. Mathematics, 9. https://doi.org/10.3390/math9040361. [BibTeX]  [PDF]
Marko Djukanovic,  Christoph Berger,  Günther R. Raidl,  & Christian Blum (2021). An A⁎ search algorithm for the constrained longest common subsequence problem. Information Processing Letters, 166, 106041. https://doi.org/10.1016/j.ipl.2020.106041. [BibTeX]  [PDF]
Christian Blum,  Marko Djukanovic,  Alberto Santini,  Hua Jiang,  Chu-Min Li,  Felip Manyà,  & Günter R. Raidl (2021). Solving Longest Common Subsequence Problems via a Transformation to the Maximum Clique Problem. Computers & Operations Research, article number 105089. https://doi.org/10.1016/j.cor.2020.105089. [BibTeX]
2020
Teddy Nurcahyadi,  & Christian Blum (2020). A New Approach for Making Use of Negative Learning in Ant Colony Optimization. Marco Dorigo, Thomas Stützle, Maria J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, & Volker Strobel (Eds.), Swarm Intelligence (pp. 16--28). Springer International Publishing. [BibTeX]
Christian Blum,  Marta Verdaguer,  Hèctor Monclús,  & Manel Poch (2020). A new optimization model for wastewater treatment planning with a temporal component. Process Safety and Environmental Protection, 136, 157 - 168. [BibTeX]
Marko Djukanovic,  Günther R. Raidl,  & Christian Blum (2020). Anytime algorithms for the longest common palindromic subsequence problem. Computers & Operations Research, 114, article number 104827. https://doi.org/10.1016/j.cor.2019.104827. [BibTeX]
Pedro Pinacho-Davidson,  & Christian Blum (2020). BARRAKUDA: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem. Mathematics, 8. https://doi.org/10.3390/math8111858. [BibTeX]  [PDF]
Marko Djukanovic,  Günther R. Raidl,  & Christian Blum (2020). Finding Longest Common Subsequences: New anytime A* search results. Applied Soft Computing, 95, 106499. https://doi.org/10.1016/j.asoc.2020.106499. [BibTeX]
Christian Blum (2020). Minimum common string partition: on solving large-scale problem instances. International Transactions in Operational Research, 27, 91--111. https://doi.org/10.1111/itor.12603. [BibTeX]
Bohan Li,  Xindi Zhang,  Shaowei Cai,  Jinkun Lin,  Yiyuan Wang,  & Christian Blum (2020). NuCDS: An Efficient Local Search Algorithm for Minimum Connected Dominating Set. Proceedings of the Twenty-Nineth International Joint Conference on Artificial Intelligence, {IJCAI-20} . International Joint Conferences on Artificial Intelligence Organization. [BibTeX]
Marko Djukanovic,  Christoph Berger,  Günther R. Raidl,  & Christian Blum (2020). On Solving a Generalized Constrained Longest Common Subsequence Problem. Nicholas Olenev, Yuri Evtushenko, Michael Khachay, & Vlasta Malkova (Eds.), Optimization and Applications (pp. 55--70). Springer International Publishing. [BibTeX]  [PDF]
Matthias Horn,  Marko Djukanovic,  Christian Blum,  & Günther R. Raidl (2020). On the Use of Decision Diagrams for Finding Repetition-Free Longest Common Subsequences. Nicholas Olenev, Yuri Evtushenko, Michael Khachay, & Vlasta Malkova (Eds.), Optimization and Applications (pp. 134--149). Springer International Publishing. [BibTeX]  [PDF]
(2020). Preface to the Special Issue on Matheuristics and Metaheuristics. International Transactions in Operational Research, 27, 5-8. https://doi.org/10.1111/itor.12702. [BibTeX]  [PDF]
Gabriela Ochoa,  Katherine Mary Malan,  & Christian Blum (2020). Search Trajectory Networks of Population-Based Algorithms in Continuous Spaces. Pedro A. Castillo, Juan Luis Jim{\\'{e}}nez Laredo, & Francisco Fern{\\'{a}}ndez Vega (Eds.), Applications of Evolutionary Computation - 23rd European Conference, EvoApplications 2020 (pp. 70--85). Springer. https://doi.org/10.1007/978-3-030-43722-0\_5. [BibTeX]  [PDF]
Dhananjay Thiruvady,  Christian Blum,  & Andreas T. Ernst (2020). Solution Merging in Matheuristics for Resource Constrained Job Scheduling. Algorithms, 13. https://doi.org/10.3390/a13100256. [BibTeX]  [PDF]
2019
Dhananjay Thiruvady,  Christian Blum,  & Andreas T. Ernst (2019). Maximising the Net Present Value of Project Schedules Using CMSA and Parallel ACO. International Workshop on Hybrid Metaheuristics (HM 2019) (pp. 16-30). Springer. https://doi.org/10.1007/978-3-030-05983-5_2. [BibTeX]
Günther R. Raidl,  Jakob Puchinger,  & Christian Blum (2019). Metaheuristic Hybrids. Michel Gendreau, & Jean-Yves Potvin (Eds.), Handbook of Metaheuristics (pp 385-417). Springer International Publishing. https://doi.org/10.1007/978-3-319-91086-4_12. [BibTeX]
Divansh Arora,  Parikshit Maini,  Christian Blum,  & Pedro Pinacho Davidson (2019). Route Planning for Cooperative Air-Ground Robots with Fuel Constraints: An Approach based on CMSA. Genetic and Evolutionary Computation Conference (GECCO 2019) (pp. 207-214). ACM Press. https://doi.org/10.1145/3321707.3321820. [BibTeX]