Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

Activity-based scheduling optimization is a combinatorial problem built on the traveling
salesman problem intending to optimize people schedules considering their trips and the …

Constrained multiobjective optimization problems (CMOPs) are challenging because of the
difficulty in handling both multiple objectives and constraints. While some evolutionary …

This article presents a survey of genetic algorithms that are designed for solving multi depot
vehicle routing problem. In this context, most of the articles focus on different genetic …

The field of complex network clustering has been very active in the past several years. In this
paper, a discrete framework of the particle swarm optimization algorithm is proposed. Based …

In this paper, a new variant of the Particle Swarm Optimization (PSO) algorithm is proposed
for the solution of the Vehicle Routing Problem with Time Windows (VRPTW). Three different …

Customized bus (CB) is an increasingly popular mode of transportation in many cities
around the world. However, studies on CB network design have mostly overlooked three …

Feature selection is a useful pre-processing technique for solving classification problems. As
an almost parameter-free optimization algorithm, the bare bones particle swarm optimization …

In the real world, there are a number of optimization problems whose search space is
restricted to take binary values; however, there are many continuous metaheuristics with …

Vehicle routing problem with time windows (VRPTW) is a pivotal problem in logistics domain
as it possesses multiobjective characteristics in real-world applications. Literature contains a …