Bin Packing with Conflicts (BPC) are problems in which items with compatibility constraints must be packed in the least number of bins, not exceeding the capacity of the bins and ensuring that non-conflicting items are packed in each bin. In this work, we introduce the Bin Packing Problem with Compatible Categories (BPCC), a variant of the BPC in which items belong to conflicting or compatible categories, in opposition to the item-by-item incompatibility found in previous literature. It is a common problem in the context of last mile distribution to nanostores located in densely populated areas. To efficiently solve real-life sized instances of the problem, we propose a Variable Neighborhood Search (VNS) metaheuristic algorithm. Computational experiments suggest that the algorithm yields good solutions in very short times while compared to linear integer programming running on a high-performance computing environment.

Cashierless stores are all the rage. You need look no further for evidence than Amazon's rapidly expanding Amazon Go chain and the tens of millions of VC dollars startups like Trigo Vision and Zippin have snatched up in the past year. Some, like Grabango, offer plug-and-play systems designed to accommodate warehouse-style installations -- i.e., stores up to 100,000 square feet. But checkout-free platforms come in all shapes and sizes, and retailers on the hunt for tech with a smaller footprint can take advantage of AiFi's latest innovation. AiFi, a Santa Clara startup that emerged from stealth in February and beat out more than 900 submissions in Visa's 2018 Everywhere contest, today unveiled the NanoStore.