This paper presents a state-of-the-art review on multi-objective metaheuristics for multi-
objective discrete optimization problems (MODOPs). The relevant literature source and their …

We present the design of an algorithm to maximize the number of bugs found for black-box
mutational fuzzing given a program and a seed input. The major intuition is to leverage white …

In order to be competitive in today's rapidly changing business world, enterprises have
transformed a centralized to a decentralized structure in many areas of decision. It brings a …

With the penetration of decentralization into factories, the production scheduling among non-
identical factories has emerged as a hot issue for industrial demand response. However …

This article studies a distributed heterogeneous hybrid flow shop scheduling problem under
nonidentical time-of-use electricity tariffs (DHHFSP-NTOU). The makespan and the total …

In recent years, the rapid development of the Internet of Things (IoT) has produced a large
amount of data that needs to be processed in a timely manner. Traditional cloud computing …

This paper integrates an estimation of distribution (EoD)-based update operator into
decomposition-based multiobjective evolutionary algorithms for binary optimization. The …

Sparse unmixing has become a popular tool for hyperspectral imagery interpretation. It
refers to finding the optimal subset of a spectral library to reconstruct the image data and …

In evolutionary algorithms, a preselection operator aims to select the promising offspring
solutions from a set of candidate offspring solutions. It is usually based on the estimated or …

As a typical model-based evolutionary algorithm, estimation of distribution algorithm (EDA)
possesses unique characteristics and has been widely applied in global optimization …