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Computational Logistics of the Vehicle Routing Problem with Time Windows. Comparative Review of application of the PSO and GA to the VRPTW.

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Vehicle Routing Problem with Time Windows

Computational Logistics of the Vehicle Routing Problem with Time Windows (VRPTW). Comparative Review of application of the solution techniques, the Particle Swarm Optimisation (PSO) algorithm and Genetic Algorithm (GA) to the VRPTW.

Conference Proceedings: https://ieeexplore.ieee.org/document/9004294

SOLUTION TECHNIQUE ALGORITHMS

The solution technique algorithms are based according to the respective references given below. The algorithms are coded using Python 3.

Genetic Algorithm for the VRPTW:

Ombuki, Beatrice, Brian J. Ross, and Franklin Hanshar. "Multi-objective genetic algorithms for vehicle routing problem with time windows." Applied Intelligence 24.1 (2006): 17-30. https://link.springer.com/content/pdf/10.1007/s10489-006-6926-z.pdf

Particle Swarm Optimisation algorithm for the VRPTW:

Gong YJ, Zhang J, Liu O, Huang RZ, Chung HS, Shi YH. Optimizing the vehicle routing problem with time windows: a discrete particle swarm optimization approach. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews). 2012 Mar;42(2):254-67. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5773510

Datasets: Solomon Benchmarking Dataset

https://www.sintef.no/projectweb/top/vrptw/solomon-benchmark/

Executing Files:

For each of the algorithms and the respective metrics ('../VRPTW_code/algorithm_Metric'), the code for the initial encoding and optimisation technique can be found in the following files:

For GA:

Initial Encoding: '../initial_encoding/main_initialEncoding.py'

Optimisation: '../main/main.py'

For PSO:

Initial Encoding: '../initial_encoding/initialEncoding_case1.py'

Optimisation: '../main/main.py'

NOTE: Initial encoding needs to be run before running the main file in order to create the initial candidate solutions.

Please note that the 'initial_encoding/initial' folder contains the initial encodings, and the '/main/final' folder contains some experiments from solving the VRPTW for datasets with 25 customers. These folders would need to be replicated to run the datasets with 50 and 100 customers. And set the 'num_customers' in the respective files to the dataset that you are considering i.e. 25, 50 and 100 customers.

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