Vehicle scheduling algorithm based on greedy tabu search

Abstract

The invention discloses a vehicle scheduling algorithm based on greedy tabu search, and the algorithm comprises the steps: establishing a vehicle scheduling basic model based on dynamic planning, solving, and obtaining a vehicle scheduling initial solution; establishing a loss function based on a tabu search algorithm to serve as a basis for iteration of an initial solution; performing local iterative search improvement based on a neighborhood structure thought to generate a plurality of reliable candidate solutions; in order to prevent local search from falling into a local optimal solution,adding various destruction operator disturbance initial solutions to enable the initial solutions to have relatively high quality; and filtering the candidate solutions according to a loss function adopted by a tabu search algorithm to obtain an optimal solution in the candidate solutions, and generating a final scheduling scheme. Cost of vehicles and drivers is considered, a scientific model algorithm, namely a greedy tabu search algorithm and a scheduling scheme for searching the minimum number of vehicles and conforming to scheduling habits, is applied, effectiveness of the algorithm is verified, and the algorithm is applied to practice.

Description

technical field [0001] The invention belongs to the technical field of electric public transport vehicle scheduling, and in particular relates to a vehicle scheduling algorithm based on greedy tabu search. Background technique [0002] Public transportation is an important mode of transportation for the public to travel, and it is also an important means to solve the problem of urban traffic congestion. Vehicle scheduling and scheduling is an important part of public transport operation management. After the bus line and line timetable are determined, vehicle scheduling and scheduling is a daily work of the bus company. Optimal scheduling of bus services can lead to significant savings in operating costs by reducing the number of vehicles and drivers required for bus companies. In addition, reasonably arrange the driver's work and rest time, so as to provide guarantee for safe and efficient bus operation. [0003] Aiming at the problem of bus scheduling, scholars at home ...

AI Technical Summary

Problems solved by technology

The optimization method uses traditional optimization models such as linear programming models, and uses algorithms such as column generation technology and branch-and-bound method. The advantage is that the obtained scheduling scheme is optimal. The disadvantage is that the algorithm runs for too long and is difficult to apply to large-scale relatively large practical problems

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