An optimization method for cooperative operation of double cranes in a storage yard

Abstract

An optimization method for the cooperative operation of double cranes in the yard, which improves the standard seagull algorithm, introduces the nonlinear weight of the fusion of cosine factors and the learning strategy of the pacesetter into the standard seagull algorithm, and improves the depth and breadth of the search in the algorithm optimization process , thereby improving the quality and efficiency of the algorithm solution, thus further improving the cooperative operation efficiency of the double cranes on the same track in the yard.

Description

technical field [0001] The invention relates to the technical field of smart storage yard applications, in particular to a method for optimizing the coordinated operation of double cranes in a storage yard. Background technique [0002] Due to the current rapid development of the Internet, people are more and more inclined to shop through e-commerce platforms, resulting in an explosive growth of e-commerce orders. The timely delivery of goods to each customer is a vivid practice of the company's "customer first" concept; For e-commerce companies that store goods in the yard, if they still use the traditional single-track single-crane operation mode of the yard, they will not be able to meet the needs of timely picking and warehousing operations for large-scale customer orders, thus affecting the customer experience. The profit of the enterprise is not conducive to the development of the enterprise. Therefore, seeking a new operation mode of the yard crane will not only help ...

AI Technical Summary

Problems solved by technology

[0004] Seagull algorithm (Seagull optimization algorithm, SOA) is a new type of swarm intelligence optimization algorithm proposed by Gaurav Dhiman and Vijaykumar in 2018. The seagull algorithm mainly simulates the migration and attack behavior of seagulls; A place suitable for living flies to another place suitable for living. Migration behavior affects the global exploration ability of the SOA algorithm; attack behavior refers to seagulls attacking and foraging for food on the ground and in the water during flight, and the attack behavior affects the SOA algorithm. Local development capability; however, the traditional seagull algorithm has the disadvantages of being prone to fall into local optimum and premature convergence. Therefore, this method improves the seagull algorithm to solve the problem of low operating efficiency of double cranes in the storage yard

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