Bicycle scheduling method used for cargo collection and delivery

Abstract

The invention discloses a bicycle scheduling method used for cargo collection and delivery. The method comprises the following steps that: obtaining the system characteristic data of a vehicle scheduling application scene, creating a collection and delivery task, and processing the system characteristic data of a collection and delivery problem into a form which conforms to composite structure construction requirements; creating a constraint used for constructing the composite structure, and a method of the constraint for constructing the composite structure, carrying out classification according to an influence form for the composite structure, randomly constructing a sorting structure, utilizing a sorting structure construction method based on the sorting structure constraint to carry out local regulation on a current sorting structure to enable the current sorting structure to meet the constraint, utilizing a grouping structure constraint to construct each group on the basis of thesorting structure, and utilizing an integral structure constraint to carry out detection and local composite structure regulation; and putting into a metaheuristic method, carrying out iterative evolution on a scheme, stopping iteration according to a termination rule, and outputting an optimal scheduling plan. By use of the method, a purpose of considering both instantaneity and transportabilityis achieved, and use requirements in a practical application scene can be met.

Description

technical field [0001] The invention relates to the technical field of intelligent dispatching, in particular to a single-vehicle dispatching method for picking up and delivering goods. Background technique [0002] Goods pick-up and delivery exist in many fields of social and economic systems, such as urban logistics distribution system, sorting system, container automatic packing system and railway station pick-up and delivery shunting system, etc. In particular, with the advancement and development of science and technology, it will face many new application areas, such as drone delivery scheduling, unmanned delivery car scheduling, and driverless taxi scheduling. Although this problem has a long history and there are many relatively mature methods, most of them tend to be theoretical research. When it comes to the application level, due to the different characteristics of the usage scenarios, the method is subject to many constraints in terms of efficiency or portability...

AI Technical Summary

Problems solved by technology

Although the heuristic method is often more advantageous in terms of efficiency, it cannot avoid the dependence on specific features, which are determined by the application scenarios. The slight differences in system characteristics in different scenarios often make the scheduling methods completely different, which makes the heuristic method Scalability is restricted, which in turn limits its scope

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