In this paper we study the vehicle routing problem with zone-based pricing where the
transporter defines a service price for all customers in a geographical zone. Each customer …

This paper presents a set of adaptive parameter control methods through reinforcement
learning for the particle swarm algorithm. The aim is to adjust the algorithm's parameters …

In this paper, we propose an evolutionary algorithm for solving the multi-robot orienteering
problem where a team of cooperative robots aims to maximize the total information collected …

Abstract The Capacitated Team Orienteering Problem (CTOP) is a challenging
combinatorial optimization problem, wherein a fleet of vehicles traverses multiple locations …

In smart cities, unmanned aerial vehicles and self-driving vehicles are gaining increased
concern. These vehicles might utilize ultra-reliable telecommunication systems, Internet …

This chapter describes a case study regarding the use of 'agile'computational intelligence for
supporting logistics in Barcelona's hospitals during the COVID-19 crisis in 2020. Due to the …

The team orienteering problem (TOP) is a well-studied optimization challenge in the field of
Operations Research, where multiple vehicles aim to maximize the total collected rewards …

Stagnation at local optima represents a significant challenge in bio-inspired optimization
algorithms, often leading to suboptimal solutions. This paper addresses this issue by …

A novel mobile charging service that utilizes vehicle-to-vehicle (V2V) charging technology
has recently been proposed as a supplement to fixed charging infrastructure (CI), enabling …

In this paper, we analyze both the deterministic and stochastic versions of a team
orienteering problem (TOP) in which rewards from customers are dynamic. The typical goal …