Abstract The Set Covering Problem (SCP) is one of the classical Karp's 21 NP-complete
problems. Although this is a traditional optimization problem, we find many papers assuming …

In this paper, we solve the Set Covering Problem with a meta-optimization approach. One of
the most popular models among facility location models is the Set Covering Problem. The …

The set covering problem is a classical optimization benchmark that finds application in
several real-world domains, particularly in line balancing production, crew scheduling, and …

Evolutionary algorithms have been used to solve several optimization problems, showing an
efficient performance. Nevertheless, when these algorithms are applied they present the …

Method: One of the main problems which we turn out to be faced on having used
metaheuristic is the difficulty of realizing a correct parametrization with the purpose to find …

Combinatorial optimization problems are very common in the real world but difficult to solve.
Among the promising algorithms that have been successful in solving these problems are …

Currently, the industry is experiencing an exponential increase in dealing with binary-based
combinatorial problems. In this sense, metaheuristics have been a common trend in the field …

The set covering problem (SCP) is an NP‐complete optimization problem, fitting with many
problems in engineering. The traditional SCP formulation does not directly address both …

Metaheuristics are a class of algorithms with some intelligence and self-learning capabilities
to find solutions to difficult combinatorial problems. Although the promised solutions are not …

Population-based metaheuristics can be seen as a set of agents that smartly explore the
space of solutions of a given optimization problem. These agents are commonly governed …