Related papers: A Carbon Aware Ant Colony System (CAACS)
Cooperative transport, the simultaneous movement of an object by multiple agents, has been widely observed in biological systems such as ant colonies, which improve efficiency and adaptability in dynamic environments. Inspired by these…
Colonies of ants are systems of interacting living organisms in which interactions between individuals and their environment can produce a reliable performance of a complex tasks without the need for centralised control. Particularly…
The past decade has seen the rapid development of the online newsroom. News published online are the main outlet of news surpassing traditional printed newspapers. This poses challenges to the production and to the consumption of those…
This paper presents the development of a tangible platform for demonstrating the practical implementation of cooperative adaptive cruise control (CACC) systems, an enhancement to the standard adaptive cruise control (ACC) concept by means…
This paper proposes a path planning algorithm for multi-agent unmanned aircraft systems (UASs) to autonomously cover a search area, while considering obstacle avoidance, as well as the capabilities and energy consumption of the employed…
Ants are very small insects.They are capable to find food even they are complete blind. The ants lives in their nest and their job is to search food while they get hungry. We are not interested in their living style, such as how they live,…
Ant Colony Optimization (ACO) is a swarm intelligence methodology utilized for solving optimization problems through information transmission mediated by pheromones. As ants sequentially secrete pheromones that subsequently evaporate, the…
The Travelling Salesman and its variations are some of the most well known NP hard optimisation problems. This paper looks to use both centralised and decentralised implementations of Evolutionary Algorithms (EA) to solve a dynamic variant…
Standard transport protocols like TCP operate as a blind, FIFO conveyor belt for data, a model that is increasingly suboptimal for latency-sensitive and interactive applications. This paper challenges this model by introducing CATS…
Robotic shepherding is a bio-inspired approach to autonomously guiding a swarm of agents towards a desired location. The research area has earned increasing research interest recently due to the efficacy of controlling a large number of…
Autonomous mobility is emerging as a new disruptive mode of urban transportation for moving cargo and passengers. However, designing scalable autonomous fleet coordination schemes to accommodate fast-growing mobility systems is challenging…
Reliable and efficient trajectory optimization methods are a fundamental need for autonomous dynamical systems, effectively enabling applications including rocket landing, hypersonic reentry, spacecraft rendezvous, and docking. Within such…
Connected and Autonomous Vehicles (CAVs) with their evolving data gathering capabilities will play a significant role in road safety and efficiency applications supported by Intelligent Transport Systems (ITS), such as Traffic Signal…
We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Cooperative Group Optimization (CGO), to show the leveraged optimization with a mixed individual and social learning. Ant colony is a simple yet efficient…
This study introduces an innovative methodology for the planning of metro network routes within the urban environment of Chennai, Tamil Nadu, India. A comparative analysis of the modified Ant Colony Optimization (ACO) method (previously…
Our research aims at developing intelligent systems to reduce the transportation-related energy expenditure of a large city by influencing individual behavior. We introduce COPTER - an intelligent travel assistant that evaluates multi-modal…
This paper proposes a hybrid genetic algorithm for solving the Multiple Traveling Salesman Problem (mTSP) to minimize the length of the longest tour. The genetic algorithm utilizes a TSP sequence as the representation of each individual,…
In this work we introduce an evolutionary strategy to solve combinatorial optimization tasks, i.e. problems characterized by a discrete search space. In particular, we focus on the Traveling Salesman Problem (TSP), i.e. a famous problem…
An adaptive traffic signal controller (ATSC) combined with a connected vehicle (CV) concept uses real-time vehicle trajectory data to regulate green time and has the ability to reduce intersection waiting time significantly and thereby…
Automated process control systems (APCS) are widely used in modern industrial enterprises. They address three key objectives: ensuring the required quality of manufactured products, ensuring process safety for people and the environment,…