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

被引:0
作者
Tasgetiren, M. Fatih [1 ]
Buyukdagli, Ozge [1 ]
Kizilay, Damla [1 ]
Karabulut, Korhan [2 ]
机构
[1] Yasar Univ, Dept Ind Engn, Izmir, Turkey
[2] Yasar Univ, Software Engn Dept, Izmir, Turkey
来源
SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT I (SEMCCO 2013) | 2013年 / 8297卷
关键词
traveling salesman problem; iterated greedy algorithm; inver-over operator; memetic algorithm; genetic algorithm; meta-heuristics; DEPENDENT SETUP TIMES; DIFFERENTIAL EVOLUTION ALGORITHM; PARTICLE SWARM OPTIMIZATION; FLOWSHOP SCHEDULING PROBLEM; LIN-KERNIGHAN; HEURISTIC ALGORITHM; GENETIC ALGORITHMS; NEURAL-NETWORK; LOCAL SEARCH; MACHINE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 52 条