Results 11 to 20 of about 305,569 (242)
Towards a Theory of Randomized Search Heuristics [PDF]
Lecture Notes in Computer Science, 2003 There is a well-developed theory about the algorithmic complexity of optimization problems. Complexity theory provides negative results which typically are based on assumptions like NP≠P or NP≠RP. Positive results are obtained by the design and analysis of clever algorithms. These algorithms are well-tuned for their specific domain.
Ingo Wegener, Wegener Ingo
exaly +3 more sources
Runtime analysis of randomized search heuristics for dynamic graph coloring [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference, 2019 We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical graph coloring problem and investigate the dynamic setting where edges are added to the current graph.
Jakob Bossek +3 more
semanticscholar +3 more sources
Computing Minimum Cuts by Randomized Search Heuristics [PDF]
Algorithmica, 2008 We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimization problems that occur as crucial subproblems in many real-world ...
Frank Neumann +2 more
semanticscholar +7 more sources
Optimizing the Classic and the Energy-Efficient Permutation Flowshop Scheduling Problem with a Hybrid Tyrannosaurus Rex Optimization Algorithm [PDF]
BiomimeticsThis paper introduces a Hybrid Tyrannosaurus Rex Optimization Algorithm (Hybrid TROA) combined with Variable Neighborhood Search (VNS), two variations of the Path Relinking strategy, and a randomized Nawaz–Enscore–Ham (NEH) heuristic to address the ...
Maria Tsiftsoglou +2 more
doaj +2 more sources
Theory of Randomized Search Heuristics: Foundations and Recent Developments [PDF]
Theory of Randomized Search Heuristics, 2011 Randomized search heuristics such as evolutionary algorithms, genetic algorithms, evolution strategies, ant colony and particle swarm optimization turn out to be highly successful for optimization in practice. The theory of randomized search heuristics, which has been growing rapidly in the last five years, also attempts to explain the success of the ...
A. Auger, Benjamin Doerr
semanticscholar +2 more sources
Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem [PDF]
Evolutionary Computation, 2016 Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget.
Samadhi Nallaperuma +2 more
semanticscholar +5 more sources
On benefits and drawbacks of aging strategies for randomized search heuristics
Theoretical Computer Science, 2011 Quite different search heuristics make use of the concept of assigning an age to search points and systematically remove search points that are too old from the search process.
T. Jansen, C. Zarges
semanticscholar +3 more sources
How randomized search heuristics find maximum cliques in planar graphs [PDF]
Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2006 Surprisingly, general search heuristics often solve combinatorial problems quite sufficiently, although they do not outperform specialized algorithms. Here, the behavior of simple randomized optimizers on the maximum clique problem on planar graphs is investigated rigorously. The focus is on the worst-, average-, and semi-average-case behaviors.
T. Storch
semanticscholar +3 more sources
Optimizing Linear Functions with Randomized Search Heuristics - The Robustness of Mutation
Symposium on Theoretical Aspects of Computer Science, 2012 The analysis of randomized search heuristics on classes of functions is fundamental for the understanding of the underlying stochastic process and the development of suitable proof techniques. Recently, remarkable progress has been made in bounding the expected optimization time of the simple (1+1) EA on the class of linear functions.
Carsten Witt
semanticscholar +6 more sources
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem [PDF]
Algorithmica, 2021 We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph.
Jakob Bossek +3 more
semanticscholar +1 more source