Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 2022

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: zajezdnia kolejowa

Sortuj według:

Ogranicz wyniki do:

Determination of Truck Maintenance Allocation Scheme Based on SA-GA

Qiu Jiandong, Ren Wei, Tang Minan, Ma Panpan, Zhang Yang

Archives of Transport

2022

Vol. 62, iss. 2

59--71

As an important department of railway transportation and production, large freight train depot is responsible for the regular overhaul and maintenance of railway trucks. The shunting operation of freight train depot covers the whole process of railway trucks entering, storing, overhauling and leaving the depot. It is an important step in the implementation of the maintenance operation. Usually, shunting personnel in the depot transport the trucks to be overhauled to the maintenance line by relying on the shunting operation plan, which is the key to determine the shunting operation plan according to the distribution relationship between vehicles and maintenance. Firstly, this paper analyzes the process of centralized shunting operation in the freight train depot and the factors affecting the time-consuming based on the research idea of flexible workshop scheduling problem. Then, on the premise that the proportion of the weight coefficient will have an impact on the time-consuming of truck busy and shunting in the shunting process, and with the goal of minimizing the time-consuming of truck maintenance busy and shunting, the allocation model between trucks and maintenance lines is established; In addition, an improved genetic algorithm is proposed to solve the established model; Finally, combined with the maintenance of railway trucks in a large freight train depot, an example analysis is carried out on this basis. The results demonstrate that using simulated annealing genetic algorithm to solve the model can obtain the allocation scheme between railway trucks and maintenance operation line. Under the influence of three different coefficients, compared with genetic algorithm, simulated annealing genetic algorithm can reduce the detention time of railway trucks in depot by 0.21%, 0.09% and 0.12% respectively, which is beneficial to reducing the detention time of maintenance vehicles in depot, It plays a positive role in improving the maintenance efficiency of trucks in the depot, and also provides new ideas for the research of railway truck shunting