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Recent work has shown the potential of ant algorithms for generation constructive hyper-heuristics. This paper extends the previous research by presenting a novel ant algorithm that is used to drive the heuristic search for a generation perturbative ...

We introduce a novel algorithm for ride-hailing services, called Predictive Leafcutter Ant optimization for Networks (PLAN), that is shown to reduce vehicular fuel costs and customer wait times, especially for clustered requests. PLAN combines ...

Previous studies have employed Ant Colony Optimisation to solve the University Course Timetabling task --- which requires the order of lecture assignments to be defined for its construction graph. Various heuristic or random ordering techniques have ...

In this paper a new population update rule for population based ant colony optimization (PACO) is proposed. PACO is a well known alternative to the standard ant colony optimization algorithm. The new update rule allows to weight different parts of the ...

The paper considers route optimization problems for unmanned aerial vehicles (UAV), which act as a team when inspecting or supporting a given set of objects in the presence of alternative and dynamic depots (starting and/or landing sites) and ...

This paper presents a new planner based on Ant Colony Optimization for Real-coded domains (ACO_R) for optimizing the trajectories of multiple Unmanned Aircraft Vehicles (UAVs) in Minimum Time Search (MTS) missions, where the UAVs have to shorten the ...

Cooperative multiagent systems are used for solving many computational hard problems. In the scientific literature, the intelligence of cooperative multiagent systems is considered at the systems' level and is based on the "intelligent problem solving" ...

Metaheuristics include a wide range of optimization algorithms. Some of them are very well known and with proven value, as they solve successfully many examples of combinatorial NP-hard problems. Some examples of Metaheuristics are Genetic Algorithms (...

In this work we present different learning strategies focused on detecting candidate solutions that are not interesting to be explored by a metaheuristic, in terms of evaluation function. We include a first step before the metaheuristic. The information ...

Swarm Intelligence metaheuristics, and among them Ant Colony Optimization (ACO), have been successfully applied worldwide to solve multiple examples of combinatorial NP-hard problems, giving good solutions in a reasonable period of time (an essential ...

We introduce Group Learning for Ant Colony Optimization applied to combinatorial optimization problems with group-structured solution encodings. In contrast to the common assignment of one pheromone value per solution component in Group Learning each ...

In testing our multi-agent cyber security system, Ant-Based Cyber Defense (ABCD) we have found that pheromone efficacy, swarm formation, and cyber-security properties of a multi-agent system can be affected by non-uniform delay times experienced by the ...

Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: ...

QoS routing problem in wireless mesh networks is a NP-complete problem, and it is hard to get the global solution with the traditional algorithm. In this paper, we adopt a novel dynamic ant genetic hybrid algorithm to solve QoS unicast routing problem ...

This paper introduces Antares, which is a bioinspired algorithm for the construction of a decentralized and self-organized P2P information system in computational grids. This algorithm exploits the properties of ant systems, in which a number of ...

This paper presents an ant system coupled with a local search applied to an over-constrained airport gate assignment problem ( AGAP ). In the airport gate assignment problem we are interested in selecting and allocating aircrafts to the gates such ...

When facing dynamic optimization problems the goal is no longer to find the extrema, but to track their progression through the space as closely as possible. Over these kind of over changing, complex and ubiquitous real-world problems, the explorative-...

In addition to the control and supervision of components and connections, network management middlewares are required to enhance reliability and efficiency of distributed systems. In this paper, we describe a modular and distributed middleware ...

Hereafter we introduce a novel algorithm for optimization in dynamic binary landscapes. The Binary Ant Algorithm (BAA) mimics some aspects of real social insects' behavior. Like Ant Colony Optimization (ACO), BAA acts by building pheromone maps over a ...

Terrestrial social insects build architecturally complex nests despite their limited sensors, minimal individual intelligence and the lack of a central control system. [3] Many of the nest structures emerge as a response of the individual insects to ...