In recent years, there has been a growing research interest in integrating machine learning
techniques into meta-heuristics for solving combinatorial optimization problems. This …

Reinforcement learning (RL), which is a class of machine learning, provides a framework by
which a system can learn from its previous interactions with its environment to efficiently …

The purpose of this study is to utilize reinforcement learning in order to improve the
performance of the Sand Cat Swarm Optimization algorithm (SCSO). In this paper, we …

During the past few years, research in applying machine learning (ML) to design efficient,
effective, and robust metaheuristics has become increasingly popular. Many of those …

The design of supply chain networks (SCNs) aims at determining the number, location, and
capacity of production facilities, as well as the allocation of markets (customers) and …

In this research, we investigate the application of machine learning techniques to
optimization problems and propose a novel integration between metaheuristics and …

This study proposes a novel bioinspired metaheuristic simulating how the coronavirus
spreads and infects healthy people. From a primary infected individual (patient zero), the …

Most credit scoring algorithms are designed with the assumption to be executed in an
environment characterized by an automatic processing of credit applications, without …

Ant Lion Optimizer (ALO) is a recent novel algorithm developed in the literature that
simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge …

With the expansion of communication in today's world and the possibility of creating
interactions between people through communication networks regardless of the distance …