The efficiency and dynamism of unmanned aerial vehicles, or drones, have presented
substantial application opportunities in several industries in the last years. Notably, logistic …

Combinatorial Optimization is an important area of computer science that has many
theoretical and practical applications. In this thesis, we present important contributions to …

This paper presents an efficient algorithm for an integrated operating room planning and
scheduling problem. It combines the assignment of surgeries to operating rooms and …

For combinatorial optimization problems, model-based approaches such as mixed-integer
programming (MIP) and constraint programming (CP) aim to decouple modeling and solving …

We address a one‐dimensional cutting stock problem where, in addition to trim‐loss
minimization, cutting patterns must be sequenced so that no more than s different part types …

We give a dynamic programming solution to the problem of scheduling scenes to minimize
the cost of the talent. Starting from a basic dynamic program, we show a number of ways to …

This paper describes a biased random‐key genetic algorithm (BRKGA) for the minimization
of the open stacks problem (MOSP). The MOSP arises in a production system scenario, and …

Many constraint problems exhibit dominance relations which can be exploited for dramatic
reductions in search space. Dominance relations are a generalization of symmetry and …

Search heuristics are of paramount importance for finding good solutions to optimization
problems quickly. Manually designing problem specific search heuristics is a time …

In this paper, we address the minimization of open stacks problem (MOSP). This problem
often appears during production planning of manufacturing industries, such as in the cutting …