In this paper, a novel modified whale optimization algorithm based on Tent chaos map and
tournament selection strategy (MWOA) was presented. The aim of the improved algorithm is …

Dynamic flexible job shop scheduling is a prominent combinatorial optimisation problem
with many real-world applications. Genetic programming has been widely used to …

It is hard to obtain sufficient fault samples in most real-world industrial scenarios. This has
raised the need of addressing the critical issue of imbalanced fault diagnosis that remains a …

In recent years, genetic programming has achieved impressive results on evolutionary
feature construction tasks. To increase search effectiveness, researchers have developed …

Evolutionary feature construction is a key technique in evolutionary machine learning, with
the aim of constructing high-level features that enhance performance of a learning algorithm …

Code bloat is a phenomenon in Genetic Programming (GP) characterized by the increase in
individual size during the evolutionary process without a corresponding improvement in …

Now-a-days researchers have diverted their attentions towards making stochastic algorithms
deterministic. This is to reduce the fruitless exploration during the search process and to give …

Fitness landscape analysis has been effectively used to analyze the characteristics of
combinatorial optimization problems (COPs) while investigating the behavior of applied …

Feature selection (FS) has garnered significant attention because of its pivotal role in
enhancing the efficiency and effectiveness of various machine learning and data mining …

With the growth of wafer size from 200 mm to 300 mm and then to 450 mm in recent years,
automatic material handling system (AMHS) has played an indispensable role in …