A recent adaptive algorithm, named Ant System, is introduced and used to solve the problem of job shop scheduling. The algorithm was first introduced by Dorigo, Maniezzo and Colorni in 1991 and is derived from the foraging and recruiting behaviour observed in an ant colony. It can be applied to combinatorial optimisation problems. This paper outlines the algorithm’s implementation and performan...

The development of distributed computations and complex systems modelling [11] leads to the creation of innovative algorithms based on interacting virtual entities, specifically for optimisation purposes within complex phenomena. Particule Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) are two of these algorithms. We propose in this paper a method called Community Swarm Optimisation...

Problems for which many objective functions are to be simultaneously optimised are widely encountered in science and industry. These multiobjective problems have also been the subject of intensive investigation and development recently for metaheuristic search algorithms such as ant colony optimisation, particle swarm optimisation and extremal optimisation. In this chapter, a unifying framework...

Transposition ciphers are a class of historical encryption algorithms based on rearranging units of plaintext according to some fixed permutation which acts as the secret key. Transpositions form a building block of modern ciphers, and applications of metaheuristic optimisation techniques to classical ciphers have preceded successful results on modern-day cryptological problems. In this paper w...

Ant Colony Optimisation algorithm a multi-agent approach to combinatorial optimisation problems is used for a simple ray tracing performed on only an ordinary bitmap of the city map. Together with the Berg’s recursive model a non-line-of-sight path loss could be calculated without any need of building database. In this way the coverage predictions for urban microcells could become extremely eas...

In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of ...

In this contribution, we propose an interactive multicriteria optimisation framework for the time and space assembly line balancing problem. The framework allows decision maker interaction by means of reference points to obtain the most interesting non-dominated solutions. The principal components of the framework are the g-dominance preference scheme and a state-of-the-art memetic multiobjecti...

This paper proposes a new approach to determining the supply chain (SC) design for a product comprising different subassemblies. There might be multiple suppliers that could supply the same components as well as many manufacturers that could assemble the product. Each of these options is differentiated by its lead time and cost. Given all the possible options the configuration problem is to sel...