Artificial ant systems (AAS) have been widely applied to solve many important industrial applications including network configuration or vehicle routing that involve constrained optimisation. In this paper, we explore the possible uses of AAS to handle layouts of graphical objects using constrained optimisation approach. In our evolving AAS, the stepwise movement of each individual ant naturall...

A mobile ad hoc network (MANET) is a non-centralised, multihop, wireless network that lacks a common infrastructure and hence it needs self-organisation. The biggest challenge in MANETs is to find a path between communicating nodes, which is the MANET routing problem. Biology-inspired techniques such as ant colony optimisation (ACO) which have proven to be very adaptable in other problem domain...

This paper describes current research on the optimisation of the pedagogical path of a student in an existing e-learning software. This optimisation is performed following the models given by a fairly recent field of Artificial Intelligence: Ant Colony Optimisation (ACO) [1,2,4]. The underlying structure of the E-learning material is represented by a graph with valued arcs whose weights are opt...

dynamic combinatorial problems poses a particular challenge to optimisation algorithms. Optimising a dynamic problem that does not notify the solver when a change has been made is very difficult for most well-known algorithms. Extremal Optimisation is a recent addition to the group of biologically inspired optimisation algorithms, while Ant Colony System has been used to solve a large variety o...

Ant Colony Optimisation (ACO) has in the past proved suitable to solve many optimisation problems. This research explores the ability of the ACO algorithm to balance two quality metrics (length and cost) in its decision making process. Results are given for a preliminary investigation based on a series of shortest path problems. It is concluded that, for these problems at least, the solution qu...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...

When used to solve traveling salesperson problems (TSP), Ant Colony Optimisation algorithms use the proximity of two nodes to determine the weight or cost of the edge connecting them. The weights counterpoint the pheromone in the state transition rule, used to determine the desirability of a certain next move. The proximity does not always reflect the desirability of the possible edge correctly...