A Populated Iterated Greedy Algorithm with Inver-Over Operator for Traveling Salesman Problem

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Date

2013

Authors

M. Fatih Tasgetiren
Ozge Buyukdagli
Damla Kizilay
Korhan Karabulut

Journal Title

Journal ISSN

Volume Title

Publisher

SPRINGER-VERLAG BERLIN

Open Access Color

Green Open Access

Yes

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No
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Average
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Average
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Average

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Abstract

In this study we propose a populated iterated greedy algorithm with an Inver-Over operator to solve the traveling salesman problem. The iterated greedy (IG) algorithm is mainly based on the central procedures of destruction and construction. The basic idea behind it is to remove some solution components from a current solution and reconstruct them in the partial solution to obtain the complete solution again. In this paper we apply this idea in a populated manner (IGP) to the traveling salesman problem (TSP). Since the destruction and construction procedure is computationally expensive we also propose an iteration jumping to an Inver-Over operator during the search process. We applied the proposed algorithm to the well-known 14 TSP instances from TSPLIB. The computational results show that the proposed algorithm is very competitive to the recent best performing algorithms from the literature.

Description

Keywords

traveling salesman problem, iterated greedy algorithm, inver-over operator, memetic algorithm, genetic algorithm, meta-heuristics, DIFFERENTIAL EVOLUTION ALGORITHM, PARTICLE SWARM OPTIMIZATION, HEURISTIC ALGORITHM, NEURAL-NETWORK, LIN-KERNIGHAN, FLOW-SHOPS, MACHINE, SEARCH, MINIMIZATION, Genetic Algorithm, Traveling Salesman Problem, Iterated Greedy Algorithm, Inver-over Operator, Memetic Algorithm, Meta-heuristics

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OpenCitations Citation Count
2

Source

4th International Conference on Swarm Evolutionary and Memetic Computing (SEMCCO)

Volume

8297

Issue

PART 1

Start Page

1

End Page

12
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3

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3

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1.3578

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