Intelligent scheduling covers various tools and techniques for successfully and efficiently
solving the scheduling problems. In this paper, we provide a survey of intelligent scheduling …

The term 'Memetic Algorithms'[74](MAs) was introduced in the late 80s to denote a family of
metaheuristics that have as central theme the hybridization of different algorithmic …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

We consider the job shop scheduling problem with fuzzy sets modelling uncertain durations
and flexible due dates. With the goal of maximising due-date satisfaction under uncertainty …

Researchers often comment on the popularity and potential of nature-inspired meta-
heuristics (NIM), however there has been a paucity of data to directly support the claim that …

Single-objective to multi-objective/many-objective optimization (SMO) is a new paradigm in
the evolutionary transfer optimization (ETO), since there are only “1+ 4” pioneering works on …

Memetic algorithms are optimization techniques based on the synergistic combination of
ideas taken from different algorithmic solvers, such as population-based search (as in …

Mobile apps that use sensors to monitor user behavior often employ resource heavy
inference algorithms that make computational offloading a common practice. However …

Abstract The Quantum Circuit Compilation Problem (QCCP) is challenging to the Artificial
Intelligence community. It was already tackled with temporal planning, constraint …

Memetic algorithms (MAs) are optimization techniques based on the orchestrated interplay
between global and local search components and have the exploitation of specific problem …