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Content Provider | ACM Digital Library |
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Author | DE Souza, Sérgio Ricado Stehling, Thiago Muniz De França Filho, Moacir F. |
Abstract | This paper presents a hybrid Particle Swarm Optimization (PSO) for solving Vehicle Routing Problem with Time Windows (VRPTW). Three versions of the algorithm were implemented. The first version is a traditional PSO. In this case, the initialization is random and the best insertion for each customer on the route is evaluated. The second version is a combination of Greedy Randomized Adaptive Search Procedure (GRASP) and Push-Forward Insertion Heuristic (PFIH) with PSO. The last version, in addition to the previous characteristics, features a mutation operator after updating speed and position of each particle. For computational experiments, the \$56\$ Solomon's instances are used and the results obtained in each version are compared with the best known results from literature. A statistical analysis indicates that the third version has a better performance than the other versions. |
Starting Page | 1489 |
Ending Page | 1490 |
Page Count | 2 |
File Format | |
ISBN | 9781450334884 |
DOI | 10.1145/2739482.2764719 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2015-07-11 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Metaheuristics Swarm intelligence Hybridization Combinatorial optimization Particle swarm optimization |
Content Type | Text |
Resource Type | Article |
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