Results 291 to 300 of about 161,336 (310)
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2-Opt Moves and Flips for Area-optimal Polygonizations
ACM Journal of Experimental Algorithmics, 2022Our work on the Computational Geometry Challenge 2019 on area-optimal polygonizations is based on two key components: (1) sampling the search space to obtain initial polygonizations and (2) optimizing such a polygonizations. Among other heuristics for obtaining polygonizations for a given set P of input points, we ...
Günther Eder +4 more
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Nonoblivious 2‐Opt heuristics for the traveling salesman problem
Networks, 2013The k‐opt heuristics are among the most common techniques for approaching the traveling salesman problem (TSP). They are used either directly or as subroutines in more sophisticated heuristics, such as the celebrated Lin–Kernighan heuristic. The value of k is typically 2 or 3.
Levin, Asaf, Yovel, Uri
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A parallel 2-opt algorithm for the Traveling Salesman Problem
Future Generation Computer Systems, 1995We present a scalable parallel local search algorithm based on data parallelism. The concept of distributed neighborhood structures is introduced, and applied to the Traveling Salesman Problem (TSP). Our parallel local search algorithm finds the same quality solutions as the classical 2-opt algorithm and has a good speed-up.
Aarts, E.H.L. +2 more
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New TSP Construction Heuristics and Their Relationships to the 2-Opt
Journal of Heuristics, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Okano, Hiroyuki +2 more
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A 2-Opt based differential evolution for global optimization
Applied Soft Computing, 2010Differential evolution (DE) is a simple and effective global optimization algorithm. It has been successfully applied to solve a wide range of real-world optimization problems. However, DE has shown some weaknesses, especially the long computational times because of its stochastic nature.
Cheng-Wen Chiang +2 more
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Probabilistic analysis of 2-opt for travelling salesman problems
International Journal of Systems Science, 1998In this paper, we propose a probabilistic model of 2-opt heuristics and study its behaviour. 2-opt is one of the most popular heuristic methods for symmetric travelling salesman problems, and has been used as the basis of various meta-heuristics such as simulated annealing and tabu search.
MASAHIRO OKADA +2 more
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A genetic algorithm with the improved 2-opt method
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005Our proposed method gives genes the priority for mutation and intersection operations. The priority of genetic locus changes by the chromosome evaluation value improvement, and shapes an effective search space area. In computational evaluation, when appropriateness priorities are given, good results are obtained.
M. Matayoshi, M. Nakarnura
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An Improved 2-Opt and ACO Hybrid Algorithm for TSP
2018 Eighth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC), 2018In this paper, an improved 2-optimization(2-opt) and Ant Colony Optimization (ACO) Hybrid Algorithm is proposed to solve the Traveling Salesman Problem (TSP). The improved scheme of ACO is to define the indirect expectation heuristic and introduce it into the calculation method of transition probability, which will reduce the effect of pheromone on ant
Yuru Zhang +5 more
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Hybrid Genetic Algorithm by Simulated Evolution using 2-opt Method
Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing and Networks / 796: Software Engineering / 792: Web-based Education, 2013In this paper, we propose a hybrid genetic algorithm by simulated evolution using 2-opt method. The proposed method uses probabilistic search by simulated evolution using 2-opt method to avoid a risk of initial convergence or local solutions, and realizes the improvement of solutions over long generations by genetic algorithm.
Hiroaki Kishizawa, Yuko Osana
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Job Scheduling using Genetic Matrix Crossover Operator with 2-Opt Inversion
Intelligent Automation & Soft Computing, 1997ABSTRACTEfficient job scheduling is important to the performance of many systems. These systems include multiprocessor platforms, employee scheduling tasks, flexible manufacturing systems, and autonomous navigation planning. We will explore applying a Genetic Algorithm (GA) strategy currently used in the Traveling Salesperson Problem (TSP) to solve the
Sidney L. Bryson +3 more
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