The permutation flowshop problem is a classic machine scheduling problem where n jobs
must be processed on a set of m machines disposed in series and where each job must visit …

This paper aims at integrating machine learning techniques into meta-heuristics for solving
combinatorial optimization problems. Specifically, our study develops a novel efficient …

Nowadays, improving the management of complex supply chains is a key to become
competitive in the twenty-first century global market. Supply chains are composed of multi …

Abstract The Permutation Flow Shop Scheduling Problem (PFSSP) is an interesting
scheduling problem that has many real-world applications. It has been widely used as a …

Influenced by the economic globalization, the distributed manufacturing has been a common
production mode. This paper considers a multiobjective distributed no-wait flow-shop …

The permutation flow shop scheduling problem (PFSP), which is one of the most important
scheduling types, is widespread in the modern industries. With the increase of scheduling …

This paper proposes a memetic algorithm (MA) with novel semi-constructive crossover and
mutation operators (MASC) to minimize makespan in permutation flowshop scheduling …

The permutation flow shop scheduling problem (PFSP) is one of the most important
scheduling types in the mass customization production with many real-world applications. It …

For decades, computer scientists have looked to nature for biologically inspired solutions to
computational problems; ranging from robotic control to scheduling optimization …

This paper investigates permutation flow shop scheduling (PFSS) problems under the
effects of position-dependent learning and linear deterioration. In a PFSS problem, there are …