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An improved multi-objective optimization genetic algorithm for solving the optimal collection data collector position and moving paths is proposed, which introduces virtual segments and hierarchical chromosome structure, improved population diversity, and custom coding and decoding.
The task of selecting an optimal collection route is a complex problem, especially for large and densely populated cities.
The optimal collection cost was €42.4 t−1.
This can be achieved through optimal collection, infiltration and storage of stormwater.
Quantification of the collection effect provides a theoretical basis for making optimal collection decisions with respect to loan accounts.
However, trials designed primarily to evaluate efficacy and safety often present challenges to the optimal collection of HSU estimates for economic models.
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Swabs negative for ERV3, presumably from sub-optimal collection, had reduced respiratory virus detection rates compared with samples containing ERV3.
After implementing the algorithm using C programming, this is run and, in few seconds, it obtains optimal (or near-optimal) collection routes that specify the collection sequence for each vehicle.
Therefore, the objective of this work was to determine the optimal sample collection methods for AIV detection based on practical variations in several aspects of AIV sample collection and transport.
In this paper, we propose an optimal MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route.
The optimal waste collection and transportation routes derived from our analysis result in 59.12% reduction in travel distance along the routine collection road network followed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com