How to solve cubing, batching, and routing problem together? I am working on an order picking project, which requires to cube the items into several totes in a trolley, then batching the totes, followed by parallel aisle picking/routing. 

The input data has some orders with items. Items have locations, 3 dimensions. Each tote has the same size. One trolley can fit 4 totes.

The cubing part could just use approximate volume. 

The goal is to create batches with planned picking route. 

The size of the problem: about 50-80 items per order. 5-10 orders during
the picking window. 

The problem is intertwined if we want to minimize the distance. Should the cubing part solved separately without considering the batching and routing? If so, is this a VRP? 

I assumed the cubing is a bin backing/multiple knapsack problem, and is first fit algorithm good enough? Which heuristic performs better?
First, you need to understand how you are going to pick. That means, in one tote, do you want only one order or multiple items of different orders can end up into one tote. If it is latter, is there any sorting or consolidation area to separate out?
Is it like one order must go into one carton?
After we have those answers, I would always prefer first cubing and then, according to our strategy, pick them, and for the optimal path, obviously use VRP.
Prefer using https://or.stackexchange.com/