This paper provides an extensive review of the popular multi-objective optimization
algorithm NSGA-II for selected combinatorial optimization problems viz. assignment …

The resource-constrained project scheduling problem is to schedule activities subject to
precedence and resource constraints such that the makespan is minimized. It has become a …

Feature selection (FS) is a critical step in data mining, and machine learning algorithms play
a crucial role in algorithms performance. It reduces the processing time and accuracy of the …

To cope with the potential shortcomings of classical fruit fly optimization algorithm (FOA), a
new version of FOA with Gaussian mutation operator and the chaotic local search strategy …

Abstract The Fruit Fly Optimization Algorithm (FOA) is a recent algorithm inspired by the
foraging behavior of fruit fly populations. However, the original FOA easily falls into the local …

Multi-skill resource-constrained project scheduling problem (MS-RCPSP) is one of the most
investigated problems in operations research and management science. In this paper, a …

Balancing between the optimization of objective functions and constraint satisfaction is
essential to handle constrained multi-objective optimization problems (CMOPs). Recently …

Solving multiobjective optimization problems (MOPs) through metaheuristic methods gets
considerable attention. Based on the classical variation operators, several enhanced …

In recent years, both distributed scheduling problem and energy-efficient scheduling have
attracted much attention. As the integration of these two problems, the distributed energy …

Semiconductor final testing scheduling problem (SFTSP) has extensively been studied in
advanced manufacturing and intelligent scheduling fields. This paper presents a Q-learning …