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- W2897979086 abstract "Fireworks algorithm (FWA) is a newly proposed swarm intelligence optimization method. It simulates the fireworks explosion process to search for the best location of sparks and has demonstrated good performance in many continuous optimization problems. In this paper, we apply FWA to the travel salesman problem (TSP), a classical discrete optimization problem. We propose a discrete fireworks algorithm for TSP by combining the general framework of FWA and current ideas for solving the TSP. We call it DFWA-TSP. In DFWA-TSP, 2-opt and 3-opt edge exchange heuristic are implemented as the basic explosion operation in FWA. An adaptive strategy is designed to decide the explosion amplitude. A particular mutation method based on insertion is also used to cover the shortage of edge exchange and a new selection method based on the quality of fireworks is adopted to pick up good fireworks efficiently. Various experiments on both TSPLIB and synthetic data have been made to compare the performance of our algorithm with current heuristic methods for TSP, such as genetic algorithm and ant colony system algorithm. We conclude that our algorithm out-performs these algorithms, especially on large-scale cases." @default.
- W2897979086 created "2018-10-26" @default.
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- W2897979086 date "2018-07-01" @default.
- W2897979086 modified "2023-09-28" @default.
- W2897979086 title "A Discrete Fireworks Algorithm for Solving Large-Scale Travel Salesman Problem" @default.
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- W2897979086 doi "https://doi.org/10.1109/cec.2018.8477992" @default.
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