Results 21 to 30 of about 34,025 (156)
, 2016 A greedy randomized adaptive search procedure (GRASP) is an itera- tive multistart metaheuristic for difficult combinatorial optimization problems. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is ...
De Santis, M. +4 more
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Scheduling parallel extrusion lines [PDF]
Journal of Project ManagementThis paper introduces the problem of scheduling jobs on parallel plastic extrusion lines where each line is composed of one or more than one extruder.
Fayez F. Boctor +2 more
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Approximating covering problems by randomized search heuristics using multi-objective models [PDF]
Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2007 The main aim of randomized search heuristics is to produce good approximations of optimal solutions within a small amount of time. In contrast to numerous experimental results, there are only a few theoretical explorations on this subject. We consider the approximation ability of randomized search heuristics for the class of covering problems and ...
Friedrich, Tobias +4 more
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More effective randomized search heuristics for graph coloring through dynamic optimization [PDF]
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020 Dynamic optimization problems have gained significant attention in evolutionary computation as evolutionary algorithms (EAs) can easily adapt to changing environments. We show that EAs can solve the graph coloring problem for bipartite graphs more efficiently by using dynamic optimization.
Bossek, J. +3 more
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A greedy randomized adaptive search procedure application to solve the travelling salesman problem
International Journal of Industrial Engineering and Management, 2019 The main objective of this article is to show an algorithm capable to find a minimal total length evaluation function roundtrip in symmetric Travelling Salesman Problem (TSP). Application of concepts related to Greedy Randomized Adaptive Search Procedure
Alvaro Neuenfeldt Júnior +1 more
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Nonparametric Comparison of Two Dynamic Parameter Setting Methods in a Meta-Heuristic Approach [PDF]
Journal of Systemics, Cybernetics and Informatics, 2007 Meta-heuristics are commonly used to solve combinatorial problems in practice. Many approaches provide very good quality solutions in a short amount of computational time; however most meta-heuristics use parameters to tune the performance of the meta ...
Seyhun HEPDOGAN +3 more
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Exponential upper bounds for the runtime of randomized search heuristics [PDF]
Theoretical Computer Science, 2020 We argue that proven exponential upper bounds on runtimes, an established area in classic algorithms, are interesting also in heuristic search and we prove several such results. We show that any of the algorithms randomized local search, Metropolis algorithm, simulated annealing, and (1+1) evolutionary algorithm can optimize any pseudo-Boolean weakly ...
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On the size of weights in randomized search heuristics [PDF]
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms, 2009 Runtime analyses of randomized search heuristics for combinatorial optimization problems often depend on the size of the largest weight. We consider replacing the given set of weights with smaller weights such that the behavior of the randomized search heuristic does not change. Upper bounds on the size of the new, equivalent weights allow us to obtain
Joachim Reichel, Martin Skutella
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Variable neighbourhood search for the minimum labelling Steiner tree problem [PDF]
, 2009 We present a study on heuristic solution approaches to the minimum labelling Steiner tree problem, an NP-hard graph problem related to the minimum labelling spanning tree problem.
Consoli, S +3 more
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IEEE AccessDriven by an unprecedented surge in freight transportation and city logistics, this paper tackles a practical variant of the famous Vehicle Routing Problem that jointly accounts for the existence of a heterogeneous fleet of vehicles, customers’ ...
Moayad Tanash, Rami As'Ad
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