A single-vehicle scheduling method for goods pickup and delivery

Abstract

The invention discloses a single-vehicle dispatching method for goods pick-up and delivery, which acquires system characteristic data of the dispatching application scene of goods pick-up and delivery vehicles, creates a pick-up and delivery task, and processes the system feature data of the pick-up and delivery problem into a form that meets the requirements for building a combined structure ;Create the constraints for constructing the combination structure and the method of constructing the combination structure, and classify according to its influence on the combination structure, construct a sorting structure randomly, and use the sorting structure construction method based on the sorting structure constraints to classify the current sorting structure The structure is locally adjusted to meet the constraints, and each group is constructed one by one by using the group structure constraints on the basis of the sorting structure, and the overall structure constraints are used to detect and partially adjust the combined structure; it is placed in a meta-heuristic method, and the scheme Iterative evolution stops iteration according to termination rules and outputs optimized scheduling plan. The invention achieves both real-time and portability, and satisfies the use requirements in actual application scenarios.

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 methods are subject to many constraints in terms of efficiency or portabili...

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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