📈 #18 Warehouses -Part II-: 3 optimization problems when picking orders

And one metaheuristic that could solve them

Buckle up, curves ahead...

My post ended up so long that I had no choice but to split it in two. So today on Feasible, I'll tell you about:

• 3 problems in grouping and picking orders in typical warehouses

• First dive into Variable Neighborhood Search, a very powerful metaheuristic

Remember why we're here today: warehouses are increasingly crucial in modern logistics, and there's a particular problem that accounts for up to 60% of the time spent in a warehouse—the order-picking process.

Moreover, Mercadona found the profitability of its online model by efficiently solving this problem.

I've also shared something about metaheuristics, especially the principles of VNS.

Today, I delve a bit deeper: I'll give you details about these problems and start scratching the surface of my favorite metaheuristic.

Let's go for it!

📦 3 problems in order picking in warehouses

When I told you that Mercadona became profitable online just by solving the order-picking problem, I was only telling you half of the story.

There are countless ways to operate a warehouse: fully automated with robots, partially automated with robots and humans coexisting, solely with humans, considering a maximum order dispatch time each day, balancing the work of all workers... You get it.

But within all these options, two parts always stand out: