Abstract
The quality of an opt imal solut ion of the Vehicle Rout ing Problem is st rongly depended on the sett ing of the configurat ion parameters of the algorithm. The paper is focused on the int roduct ion of hyperparameter search for solving the Vehicle Rout ing Problem using a HyperLoom plat form for defining and execut ing scient ific pipelines in a dist ributed environment . To give a concrete example, we focused on Periodic Vehicle Rout ing Problem for the waste collect ion. HyperLoom plat form was used to define and execute the hyperparameters sweep pipeline. The heurist ic algorithm was tested on a real benchmark of the waste collect ion in Ostrava, Czech Republic. The aim of our ca se was to effect ively combine the minimizat ion of the total t ravelled distance and the opt imizat ion of the fairness of the routes in terms of the standard deviat ion of a tour length. The waste collect ion problem was very extensive and computat ionally demanding, so it was necessary to use high performance comput ing architecture for test ing a large number of different sett ings of configurat ion parameters. The experiments were run on the supercomputer Salomon operated by IT4Innovations Nat ional Supercomput ing Center in the Czech Republic.
Highlights
In 2017, the Czech Republic p roduced 34.5 million tonnes of all waste, of which 1.5 million tonnes of hazardous waste
The goal of our work was to optimize the fairness of the routes in terms of standard deviation of a tour length and to minimize the total travelled d istance
We solved this problem by taking the standard deviation as a priority parameter for minimizing
Summary
In 2017, the Czech Republic p roduced 34.5 million tonnes of all waste, of which 1.5 million tonnes of hazardous waste. The Czech Republic is very intensively engaged in waste recycling. Heuristic and metaheuristic algorithms are used to solve the problem of waste collection. These algorithms need to set the configuration parameters that improve the quality of the provided solution. Nine configuration parameters for each type of waste need to be set. Using HyperLoo m p ipeline we are able to sweep through large parameter spaces and discover the optimal solution for the heuristic algorith m. The waste collection problem is very extensive and computationally demanding, so it is necessary to use high performance computing (HPC) architecture for testing a large nu mber of d ifferent settings of configuration parameters. The experiments were run on the supercomputer Salomon operated by IT4Innovations
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