Development of an innovative prototype generator of a driver’s work plan in collective transport systems based on evolutionary algorithms. (Q81347): Difference between revisions

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(‎Removed claim: summary (P836): On SA 42799 (2015/X), the project is commissioned by R & D to develop a new service based on the unique evolutionary algorithm of the drivers’ work plan in the collective transport management systems.The service will be based on a timetable based on input data on a whole series of variables, such as drivers, vehicles, timetable, timetable, peak hours, working conditions resulting from drivers’ working regulations, hourly rates for statutory wo...)
Property / summary
On SA 42799 (2015/X), the project is commissioned by R & D to develop a new service based on the unique evolutionary algorithm of the drivers’ work plan in the collective transport management systems.The service will be based on a timetable based on input data on a whole series of variables, such as drivers, vehicles, timetable, timetable, peak hours, working conditions resulting from drivers’ working regulations, hourly rates for statutory working hours and overtime, formal-legal conditions in the carrier and many others.The aim is to plan for the work of all drivers with a focus on the number of hours compatible with the m-CA standard in order to achieve the minimum cost of the service plan for m-ca and to ensure that the number of unscheduled traffic is minimised (or the number of unscheduled traffic is filled in every day).In addition, the important functionalities being developed within the design of the solution are to:evenly spread the number of working days on Saturdays and Sundays and public holidays, and a balanced distribution of the number of “provisions” for the different days of the first and second changes.The solutions currently on offer on the market are imperfect because they are based on cloud-algorithm algorithms.These methods are myurtic (i.e. proxy solutions) and the calculation time is very long.In large data sets (large urban agglomerations) this time is not acceptable.The research problem for the NP, which is planned to be completed by means of an evolutionary approach, is being explored with a much wider range of options in order to find a solution to the best possible solution.The traditional algorithms retained by the anne make the best choices locally without examining the consequences of these elections in the next steps.The service will allow the service to reduce the monthly costs which are generated by the necessary resources for the provision of transport services (in particular the necessary drivers and flo). (English)
 
Property / summary: On SA 42799 (2015/X), the project is commissioned by R & D to develop a new service based on the unique evolutionary algorithm of the drivers’ work plan in the collective transport management systems.The service will be based on a timetable based on input data on a whole series of variables, such as drivers, vehicles, timetable, timetable, peak hours, working conditions resulting from drivers’ working regulations, hourly rates for statutory working hours and overtime, formal-legal conditions in the carrier and many others.The aim is to plan for the work of all drivers with a focus on the number of hours compatible with the m-CA standard in order to achieve the minimum cost of the service plan for m-ca and to ensure that the number of unscheduled traffic is minimised (or the number of unscheduled traffic is filled in every day).In addition, the important functionalities being developed within the design of the solution are to:evenly spread the number of working days on Saturdays and Sundays and public holidays, and a balanced distribution of the number of “provisions” for the different days of the first and second changes.The solutions currently on offer on the market are imperfect because they are based on cloud-algorithm algorithms.These methods are myurtic (i.e. proxy solutions) and the calculation time is very long.In large data sets (large urban agglomerations) this time is not acceptable.The research problem for the NP, which is planned to be completed by means of an evolutionary approach, is being explored with a much wider range of options in order to find a solution to the best possible solution.The traditional algorithms retained by the anne make the best choices locally without examining the consequences of these elections in the next steps.The service will allow the service to reduce the monthly costs which are generated by the necessary resources for the provision of transport services (in particular the necessary drivers and flo). (English) / rank
Normal rank
 

Revision as of 11:59, 14 October 2020

Project in Poland financed by DG Regio
Language Label Description Also known as
English
Development of an innovative prototype generator of a driver’s work plan in collective transport systems based on evolutionary algorithms.
Project in Poland financed by DG Regio

    Statements

    country
    Poland
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    EU contribution
    327,250.0 zloty
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    78,540.0 Euro
    exchange rate to Euro
    0.24 Euro
    point in time
    13 January 2020
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    budget
    385,000.0 zloty
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    92,400.0 Euro
    exchange rate to Euro
    0.24 Euro
    point in time
    13 January 2020
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    co-financing rate
    85.0 percent
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    start time
    1 October 2019
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    end time
    30 September 2020
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    beneficiary name (string)
    ITS TECHNOLOGY – SOLVEO SP. Z O. O. SP. K.
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    beneficiary
    Q2511877
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    summary
    SA 42799(2015/X) Przedmiotem projektu jest zlecenie prac B+R mających na celu opracowanie prototypu nowej usługi opartej o unikalne algorytmy ewolucyjne generatora planu pracy kierowców w systemach zarządzania transportem zbiorowym. Usługa będzie opierać się na generowaniu harmonogramu na podstawie danych wejściowych, dotyczących całego szeregu zmiennych, takich jak kierowcy, pojazdy, kalendarz przewozów, rozkład jazdy, godziny szczytu, warunki pracy wynikające z regulaminu pracy kierowców, stawki godzinowe za regulaminowy czas pracy i za nadgodziny, uwarunkowania formalno-prawne rynku, na którym działa przewoźnik i wiele innych. Celem jest zaplanowanie pracy wszystkim kierowcom dokładnie na ilość godzin zgodną z normą godzin m-ca, tak aby osiągnąć minim. koszt realizacji planu przewozów dla m-ca, oraz zapewnić minim. ilość niezaplanowanych w harmon. zadań przewozowych (lub zapewnić obsadę wszystkich zadań przewozowych w każdym dniu miesiąca). Dodatkowo istotnymi funkcjonalnościami opracowywanego w ramach projektu rozwiązania mają być: równomierny rozkład ilości dni pracy w soboty i niedziele i święta oraz równomierny rozkład ilości „rezerw” w poszczególne dni na I zmianie i II zmianie. Obecnie oferowane na rynku rozwiązania są niedoskonałe ponieważ opierają się na algorytmach zachłannych. Są to metody heurystyczne (czyli dają rozwiązania przybliżone) a czas obliczeń jest bardzo długi. W dużych zestawach danych (duże aglomeracje miejskie) czas ten jest nieakceptowalny. Problem badawczy NP - zupełny planowany do rozwiązania poprzez Algor. ewolucyjne analizują znacznie szerszy zakres dopuszczalnych rozwiązań w celu znalezienia rozwiązania optymalnego. Tradycyjne algorytmy zachłanne dokonują decyzji lokalnie optymalnych bez badania skutków tych wyborów w kolejnych krokach. Użytkownikowi końc. usługa pozwoli na ograniczenie kosztów miesięcznych jakie generują zasoby niezbędne do świadczenia usług transportowych (przede wszystkim liczba niezbędnych kierowców oraz flo (Polish)
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    Identifiers

    Polish Kohesio ID
    POIR.02.03.02-18-0014/19
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