We review the most important mathematical models and algorithms developed for the exact
solution of the one-dimensional bin packing and cutting stock problems, and experimentally …

Grouping problems are combinatorial optimization problems, most of them NP-hard, related
to the partition of a set of items into different groups or clusters. Given their numerous real …

Many combinatorial optimization problems include a grouping (or assignment) phase
wherein a set of items are partitioned into disjoint groups or sets. Introduced in 1994, the …

In recent years, efficient logistics has become indispensable, and using unmanned aerial
vehicles (UAVs) or drones is promising for considerably reducing the cost and time required …

The online bin packing problem is a well-known bin packing variant and which requires
immediate decisions to be made for the placement of a lengthy sequence of arriving items of …

We propose a variant of orthogonal matching pursuit (OMP), called LoCOMP, for scalable
sparse signal approximation. The algorithm is designed for shift-invariant signal dictionaries …

Online bin-packing is a well-known problem in which immediate decisions must be made
about the placement of items with various sizes into fixed capacity bins. The associated …

Grouping problems are hard to solve combinatorial optimisation problems which require
partitioning of objects into a minimum number of subsets while a given objective is …

Hyper-heuristics are aimed at providing a generalized solution to optimization problems
rather than producing the best result for one or more problem instances. This paper …

Online bin packing requires immediate decisions to be made for placing an incoming item
one at a time into bins of fixed capacity without causing any overflow. The goal is to …