Multi-Mobile Route Planning for Reduced Picking Wait Time
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Solution Overview
Problem
The low moving speed of mobile devices in logistics limits the picking efficiency as order pickers have to wait for the devices to arrive at each stopping position, leading to reduced productivity due to the time consumed in moving between positions.
Innovation Solution
A route planning method that selects multiple mobile devices and allocates stopping positions based on a passing sequence, allowing other devices to move to their positions in advance while one device waits, thereby reducing the time spent on each stop.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single mobile device is used for picking, then the system is simple to manage, but the picking efficiency is reduced due to waiting time at each stopping position
Solution Approach 1:
The system performs preliminary actions by having mobile devices advance to their stopping positions before the order picker arrives. The route planning algorithm calculates optimal routes and stopping positions in advance, allowing mobile devices to move ahead and wait at designated locations, thereby eliminating the waiting time that would otherwise occur when the picker reaches each position.
Solution Approach 2:
The system segments the picking task by dividing it among multiple mobile devices, each responsible for specific stopping positions along the route. The route is divided into multiple segments with designated stopping positions, and different mobile devices are assigned to different segments, allowing parallel execution of picking operations.
2Productivity
If multiple mobile devices are deployed to reduce waiting time, then picking efficiency improves, but device complexity and coordination difficulty increase
Solution Approach 1:
The route planning system serves multiple functions simultaneously: it calculates optimal routes, determines stopping positions, allocates tasks to multiple mobile devices, and coordinates their movements. This multi-functional approach consolidates what would otherwise require separate systems into a single unified platform, managing complexity rather than increasing it.
Solution Approach 2:
The system dynamically adjusts route planning and stopping position allocation based on real-time conditions. The route planning algorithm can recalculate and reassign stopping positions to different mobile devices as they complete their tasks, providing adaptive coordination that manages system complexity through flexibility rather than rigid predetermined assignments.
Data Source
AI summary
Disclosed are a route planning method and device, equipment and a storage medium. The method comprises: selecting at least two mobile devices from a plurality of mobile devices; determining routes of the at least two mobile devices and a plurality of stopping positions on the routes to stop; and cross-allocating the plurality of stopping positions to the at least two mobile devices according to a passing sequence of the plurality of stopping positions on the routes. By adopting this method, when any one of the at least two mobile devices moves to its own stopping position to wait, other mobile devices can move to their own stopping positions in advance to wait. In this way, the time consumed for each mobile device to move to the corresponding stopping position can be reduced.