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In press

• [91] C. Blum. Construct, Merge, Solve and Adapt. Application to the Minimum Global Domination Problem Transactions in Operations Research (TOP), 2024. In press. (JCR, Q3, IF: 1.5)

• [90] J. Reixach, C. Blum. How to improve "Construct, Merge, Solve and Adapt"? Use Reinforcement Learning! Annals of Operations Research, 2024. In press. (JCR, Q1, IF: 4.4)

• [89] J. Reixach, C. Blum, M. Djukanovic, G.R. Raidl. A Biased Random Key Genetic Algorithm for Solving the Longest Common Square Subsequence Problem. IEEE Transactions on Evolutionary Computation, 2024. In press. (JCR, Q1, IF: 14.3)

2024

• [88] M.A. Akbay, C. Blum, C.B. Kalayci. CMSA Based on Set Covering Models for Packing and Routing Problems Annals of Operations Research, 343, pages 1-38, 2024. (JCR, Q1, IF: 4.4)

• [87] N. Nakhjiri, M. Salamo, M. Sanchez-Marre, C. Blum, J.C. Morales. Forgetful Swarm Optimization for Astronomical Observation Scheduling IEEE Access, 12, pages 171644-171661, 2024. (JCR, Q2, IF: 3.4)

• [86] C. Blum. Ant Colony Optimization: A Bibliometric Review Physics of Life Reviews, 41, pages 87-95, 2024. (JCR, Q1, IF: 13.7)

• [85] P. Pinacho Davidson, C. Blum, M.A. Pinninghoff, R. Contreras. Extension of CMSA with a Learning Mechanism: Application to the Far from Most String Problem. International Journal of Computational Intelligence Systems, 17, article number 109, 2024. (JCR, Q3, IF: 2.9)

• [84] E.G. Morquecho, S.P. Torres, F. Astudillo-Salinas, H. Ergun, D. Van Hertem, C.A. Castro, C. Blum. Comparison of an Improved Metaheuristic and Mathematical Optimization Based Methods to Solve the Static AC TNEP Problem. IEEE Transactions on Power Systems, 39(2):3240--3256, 2024, (JCR, Q1, IF: 6.6)

• [83] R.M. Rosati, S. Bouamama, C. Blum. Multi-constructor CMSA for the maximum disjoint dominating sets problem. Computers and Operations Research, 161, article number 106450, 2024. (JCR, Q1, IF: 4.6)

• [82] D.R. Thiruvady, S. Nguyen, C. Blum, A. Ernst. An efficient merge search matheuristic for maximising net present value in project scheduling. International Journal of Operational Research, 51(1), 104--127, 2024.

2023

• [81] M. Djukanovic, A. Kartelj, C. Blum. Self-adaptive CMSA for solving the multidimensional multi-way number partitioning problem. Expert Systems with Applications, 232, article number 120762, 2023. (JCR, Q1, IF: 8.5)

• [80] C. Chacon Sartori, C. Blum, G. Ochoa. STNWeb: A new visualization tool for analyzing optimization algorithms. Software Impacts, 17, article number 100558, 2023. (JCR, Q3, IF: 2.1)

• [79] G. Rodriguez Corominas, M.J. Blesa, C. Blum. AntNetAlign -- A software package for Network Alignment. Software Impacts, 15, article number 100476, 2023. (JCR, Q3, IF: 2.1)

• [78] G. Rodriguez Corominas, M.J. Blesa, C. Blum. AntNetAlign: Ant Colony Optimization for Network Alignment. Applied Soft Computing, 132, article number 109832, 2023. (JCR, Q1, IF: 6.725)

2022

• [77] C. Blum, A. Eremeev, Y. Zakharova. Hybridizations of Evolutionary Algorithms with Large Neighborhood Search. Computer Science Review, 46, article number 100512, 2022. (JCR, Q1, IF: 8.757)

• [76] T. Nurcahyadi, C. Blum, F. Manya. Negative Learning Ant Colony Optimization for MaxSAT. International Journal of Computational Intelligence Systems, 15, article number 71, 2022. (JCR, Q3, IF: 2.259)

• [75] M.A. Akbay, A. Lopez Serrano, C. Blum. A Self-Adaptive Variant of CMSA: Application to the Minimum Positive Influence Dominating Set Problem. International Journal of Computational Intelligence Systems, 15, article number 44, 2022. (JCR, Q3, IF: 2.259)

• [74] M. Djukanovic, A. Kartelj, D. Matic, M. Grbic, C. Blum, G.R. Raidl. Graph Search and Variable Neighborhood Search for Finding Longest Common Subsequences in Artificial and Real Gene Sequences. Applied Soft Computing, article number 108844, 2022. (JCR, Q1, IF: 6.725)

• [73] J. Perez, J.L. Flores, C. Blum, J. Cerquides, A. Abuin. Optimization Techniques and Formal Verification for the Software Design of Boolean Algebra Based Safety-Critical Systems. IEEE Transactions on Industrial Informatics, 18(1), pages 620-630, 2022. (JCR, Q1, IF: 10.215)

• [72] S. Bouamama, C. Blum, P. Pinacho-Davidson. A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime . Sensors, 22(5), article number 1804, 2022. (JCR, Q1, IF: 3.576)

• [71] M.A. Akbay, C.B. Kalayci, C. Blum, O. Polat. Variable Neighborhood Search for the Two-Echelon Electric Vehicle Routing Problem with Time Windows. Applied Sciences, 12(3), article number 1014, 2022. (JCR, Q2, IF: 2.679)

2021

• [70] G. Ochoa, K. Malan, C. Blum. Search trajectories illuminated. ACM SIGEVOlution, 14(2), pages 1-5, 2021.

• [69] G. Ochoa, K. Malan, C. Blum. Search trajectory networks: A tool for analysing and visualising the behaviour of metaheuristics. Applied Soft Computing, 109, article number 107492, 2021. (JCR, Q1, IF: 6.725)

• [68] B. Nikolic, A. Kartelj, M. Djukanovic, M. Grbic, C. Blum, G.R. Raidl. Solving the Longest Common Subsequence Problem Concerning Non-Uniform Distributions of Letters in Input Strings. Mathematics, 9(13), article number 1515, 2021. (JCR, Q1, IF: 2.258)

• [67] T. Nurcahyadi, C. Blum. Adding Negative Learning to Ant Colony Optimization:A Comprehensive Study. Mathematics, 9(4), article number 361, 2021. (JCR, Q1, IF: 2.258)

• [66] F. Bistaffa, C. Blum, J. Cerquides, A. Farinelli, J.A. Rodriguez Aguilar. A Computational Approach to Quantify the Benefits of Ridesharing for Policy Makers and Travellers. IEEE Transactions on Intelligent Transportation Systems, 22(1), 119--130, 2021. (JCR, Q1, IF: 6.492)

• [65] M. Djukanovic, G.R. Raidl, C. Blum. An A* Search Algorithm for the Constrained Longest Common Subsequence Problem. Information Processing Letters, 166, article number 106041, 2021. (JCR, Q4, IF: 0.959)

• [64] C. Blum, G. Ochoa. A comparative analysis of two matheuristics by means of merged local optima networks. European Journal of Operational Research, 290(1), 36--56, 2021. (JCR, Q1, IF: 5.334)

• [63] C. Blum, M. Djukanovic, A. Santini, H. Jiang, C.-M. Li, F. Manyà, G.R. Raidl. Solving longest common subsequence problems via a transformation to the maximum clique problem. Computers and Operations Research, 125, article number 105089, 2021. (JCR, Q2, IF: 4.008)

• [62] S. Balbal, S. Bouamama, C. Blum. A Greedy Heuristic for Maximizing the Lifetime of Wireless Sensor Networks Based on Disjoint Weighted Dominating Sets. Algorithms, 14(6), article number 170, 2021.

• [61] S. Bouamama, C. Blum. An Improved Greedy Heuristic for the Minimum Influence Dominating Set Problem in Social Networks. Algorithms, 14(3), article number 79, 2021.

2020

• [60] P. Pinacho Davidson, C. Blum. BARRAKUDA: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem. Mathematics, 8(11), article number 1858, 2020. (JCR, Q1, IF: 1.747)

• [59] M. Djukanovic, G.R. Raidl, C. Blum. Finding Longest Common Subsequences: New anytime A* search results. Applied Soft Computing, 95, article number 106499, 2020. (JCR, Q1, IF: 5.472)

• [58] C. Blum, M. Verdaguer, H. Montclús, M. Poch. A new optimization model for wastewater treatment planning with a temporal component. Process Safety and Environmental Protection, 136:157--168, 2020. (JCR, Q1, IF: 4.966)

• [57] M. Djukanovic, G.R. Raidl, C. Blum. Anytime Algorithms for the Longest Common Palindromic Subsequence Problem. Computers and Operations Research, 114, article number 104827, 2020. (JCR, Q2, IF: 3.424)

• [56] C. Blum. Minimum Common String Partition: On Solving Large-Scale Problem Instances. International Transactions in Operational Research, 27(1):91--111, 2020. (JCR, Q2, IF: 2.987)

• [55] D. Thiruvady, C. Blum, A.T. Ernst. Solution Merging in Matheuristics for Resource Constrained Job Scheduling. Algorithms, 13(10), article number 256, 2020.

2019

• [54] M. Horn, G.R. Raidl, C. Blum. Job Sequencing with One Common and Multiple Secondary Resources: An A*/Beam Search Based Anytime Algorithm. Artificial Intelligence, 277, article number 103173, 2019. (JCR, Q1, IF: 6.628)

• [53] E. Andrejczuk, F. Bistaffa, C. Blum, J.A. Rodriguez-Aguilar, C. Sierra. Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams. Knowledge-Based Systems, 182, article number 104799, 2019. (JCR, Q1, IF: 5.921)

• [52] S. Bouamama, C. Blum, J.-G. Fages. An Algorithm Based on Ant Colony Optimization for the Minimum Connected Dominating Set Problem. Applied Soft Computing, 80:672--686, 2019. (JCR, Q1, IF: 5.472)

2018

• [51] C. Blum, M.J. Blesa. A comprehensive comparison of metaheuristics for the repetition-free longest common subsequence problem. Journal of Heuristics, 24(3):551--579, 2018.

• [50] C. Blum. ILP-Based Reduced Variable Neighborhood Search for Large-Scale Minimum Common String Partition. Electronic Notes in Discrete Mathematics , 66:15--22, 2018.

• [49] P. Pinacho, C. Blum, J.A. Lozano. The Weighted Independent Domination Problem: Integer Linear Programming Models and Metaheuristic Approaches. European Journal of Operational Research, 265(3):860--871, 2018.

• [48] C. Blum, M.J. Blesa. Hybrid Techniques Based on Solving Reduced Problem Instances for a Longest Common Subsequence Problem. Applied Soft Computing, 62:15--28, 2018.

2017

• [47] D. Chalupa, C. Blum. Mining k-Reachable Sets in Real-world Networks Using Domination in Shortcut Graphs. Journal of Computational Science, 22:1--14, 2017.

• [46] E. Lizarraga, M.J. Blesa, C. Blum, G.R. Raidl. Large Neighborhood Search for the Most Strings With Few Bad Columns Problem. Soft Computing, 21(17):4901--4915, 2017.

2016

• [45] S. Bouamama, C. Blum. A Hybrid Algorithmic Model for the Minimum Weight Dominating Set Problem. Simulation Modelling Practice and Theory, 64:57--68, 2016.

• [44] C. Blum, P. Pinacho, M. Lopez-Ibanez, J.A. Lozano. Construct, Merge, Solve & Adapt: A New General Algorithm For Combinatorial Optimization. Computers & Operations Research, 68:75--88, 2016.

• [43] C. Blum, G.R. Raidl. Computational Performance Evaluation of Two Integer Linear Programming Models for the Minimum Common String Partition Problem. Optimization Letters, 10(1):189--205, 2016.

2015

• [42] C. Blum, B. Calvo, M. J. Blesa. FrogCOL and FrogMIS: New Decentralized Algorithms for Finding Large Independent Sets in Graphs. Swarm Intelligence, 9(2):205--227, 2015.

• [41] C. Blum, B. Calvo. A Matheuristic for the Minimmum Weight Rooted Arborescence Problem. Journal of Heuristics, 21(4):479--399, 2015.

• [40] C. Blum, J.A. Lozano and P. Pinacho Davidson. An Artificial Bioindicator System for Network Intrusion Detection. Artificial Life, 21(2):93--118, 2015.

• [39] C. Garcia, C. Blum, F. J. Rodriguez, and M. Lozano. The Firefighter Problem: Empirical Results on Random Graphs. Computers & Operations Research, 60, 55--66, 2015.

• [38] C. Blum, J.A. Lozano and P. Pinacho Davidson. Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem. European Journal of Operational Research, 242(3):769--777, 2015.

2014

• [37] H. Hernandez and C. Blum. FrogSim: Distributed Graph Coloring in Wireless Ad Hoc Networks -- An Algorithm Inspired by the Calling Behavior of Japanese Tree Frogs. Telecommunication Systems, 55(2):211--223, 2014.

2013

• [36] M. Lopez-Ibanez, C. Blum, J.W. Ohlmann and B.W. Thomas The Travelling Salesman Problem with Time Windows: Adapting Algorithms from Travel-time to Makespan Optimization. Applied Soft Computing, 13(9):3806--3815, 2013.

• [35] F. J. Rodriguez, M. Lozano, C. Blum and C. Garcia. An Iterated Greedy Algorithm for the Large-Scale Unrelated Parallel Machines Scheduling Problem. Computers & Operations Research, 40(7):1829--1841, 2013.

• [34] P. J. Copado, G. Guillen and C. Blum. Large neighbourhood search applied to the efficient solution of spatially explicit strategic supply chain management problems. Computers & Chemical Engineering, 49(11):114--126, 2013.

2012

• [33] H. Hernandez and C. Blum. Distributed Ant Colony Optimization for Minimum Energy Broadcasting in Sensor Networks with Realistic Antennas. Computers & Mathematics with Applications, 64(12):3683--3700, 2012.

• [32] F. J. Rodriguez, C. Blum, C. Garcia and M. Lozano. GRASP with path-relinking for the non-identical parallel machine scheduling problem with minimising total weighted completion times. Annals of Operations Research, 201(1):383--401, 2012.

• [31] H. Hernandez and C. Blum. Distributed Graph Coloring: An Approach Based on the Calling Behavior of Japanese Tree Frogs. Swarm Intelligence, 6(2):117--150, 2012.

• [30] S. Bouamama, C. Blum and A. Boukerram. A Population-Based Iterated Greedy Algorithm for the Minimum Weight Vertex Cover Problem. Applied Soft Computing, 12(6):1632--1639, 2012.

• [29] V. Hemmelmayr, V. Schmid and C. Blum. Variable Neigbhourhood Search for the Variable Sized Bin Packing Problem. Computers & Operations Research, 39(5):1097--1108, 2012.

• [28] A. Roli, S. Benedettini, T. Stuetzle and C. Blum. Large Neighbourhood Search Algorithms for the Founder Sequence Reconstruction Problem. Computers & Operations Research, 39(2):213--224, 2012.

2011

• [27] C. Blum. Iterative Beam Search for Simple Assembly Line Balancing with a Fixed Number of Work Stations. Statistics and Operations Research Transactions, 35(2):145--164, 2011.

• [26] H. Hernandez and C. Blum. Minimum Energy Broadcasting in Wireless Sensor Networks: An Ant Colony Optimization Approach For a Realistic Antenna Model. Applied Soft Computing, 11(8):5684--5694, 2011.

• [25] H. Hernandez and C. Blum. Foundations of ANTCYCLE: Self-Synchronized Duty-Cycling in Mobile Sensor Networks. The Computer Journal, 54(9):1427--1448, 2011.

• [24] E. Turetgen, G. Gonzalez, C. Blum and P. Fua. Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization with Geometric Priors. Neuroinformatics, 9(2-3):279--302, 2011.

• [23] C. Blum, J. Puchinger, G. Raidl and A. Roli. Hybrid Metaheuristics in Combinatorial Optimization: A Survey. Applied Soft Computing, 11(6):4135--4151, 2011.

• [22] C. Blum and C. Miralles. On solving the assembly line worker assignment and balancing problem via beam search. Computers & Operations Research, 38(1):328--339, 2011.

2010

• [21] M. Mastrolilli and C. Blum. On the use of different types of knowledge in metaheuristics based on constructing solutions. Engineering Applications of Artificial Intelligence, 23(5):650--659, 2010.

• [20] M. Lopez and C. Blum. Beam-ACO for the travelling salesman problem with time windows. Computers & Operations Research, 37(9):1570--1583, 2010.

2009

• [19] H. Hernandez and C. Blum. Ant Colony Optimization for Multicasting in Wireless Ad Hoc Networks. Swarm Intelligence, 3(2):125--148, 2009.

• [18] C. Blum, M. J. Blesa, and M. Lopez. Beam Search for the Longest Common Subsequence Problem. Computers & Operations Research, 36(12):3178--3186, 2009.

2008

• [17] C. Blum. Beam-ACO for simple assembly line balancing. INFORMS Journal on Computing, 20(4):618--627, 2008.

• [16] C. Blum, M. Yabar, and M. J. Blesa. An ant colony optimization algorithm for DNA sequencing by hybridization. Computers & Operations Research, 35, 3620-3635, 2008.

2007

• [15] M.J. Blesa and C. Blum. Finding edge-dijoint paths in networks be means of artificial ant colonies. Journal of Mathematical Modelling and Algorithms, 6(3):361-391, 2007.

• [14] K. Socha, and C. Blum. An ant colony optimization algorithm for continuous optimization: An application to feed-forward neural network training. Neural Computing & Applications, 16(3):235-248, 2007.

• [13] C. Blum. Revisiting dynamic programming for finding optimal subtrees in trees. European Journal of Operational Research, 177(1):102-115, 2007.

• [12] C. Blum. Iterated local search and constructive heuristics for error correcting code design. International Journal of Innovative Computing and Applications, 1(1):14-22, 2007.

2005

• [11] D. Merkle and C. Blum. Swarm Intelligence -- An optimization-based introduction. Künstliche Intelligenz, 4:5-10, 2005.

• [10] C. Blum. Beam-ACO---Hybridizing ant colony optimization with beam search: An application to open shop scheduling. Computers & Operations Research, 32(6):1565-1591, 2005.

• [09] C. Blum and M.J. Blesa. New metaheuristic approaches for the edge-weighted k-cardinality tree problem. Computers & Operations Research, 32(6):1355-1377, 2005.

• [08] C. Blum and M. Dorigo. Search bias in ant colony optimization: On the role of competition-balanced systems. IEEE Transactions on Evolutionary Computation, 9(2):159-174, 2005.

• [07] C. Blum. Ant colony optimization: Introduction and recent trends. Physics of Life Reviews, 2(4):353-373, 2005.

• [06] M. Dorigo and C. Blum. Ant colony optimization theory: A survey. Theoretical Computer Science, 344(2-3):243-278, 2005.

2004

• [05] C. Blum and M. Dorigo. The hyper-cube framework for ant colony optimization. IEEE Transactions on Systems, Man, and Cybernetics -- Part B, 34(2):1161-1172, 2004.

• [04] C. Blum and M. Sampels. An ant colony optimization algorithm for shop scheduling problems. Journal of Mathematical Modelling and Algorithms, 3(3):285-308, 2004.

2003

• [03] C. Blum and M. Ehrgott. Local search algorithms for the k-cardinality tree problem. Discrete Applied Mathematics, 128:511-540, 2003. Selected for the Editors' choice volume of 2003.

• [02] C. Blum and A. Roli. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys, 35(3):268-308, 2003.

1998

• [01] J. Rahmel, C. Blum, and P. Hahn. Diagnosis of finger dysfunction caused by ulnar nerve lesions. Journal of Intelligent Systems, 8(1/2), 1998.