Browsing by Author "Bernardino, Eugénia Moreira"
Now showing 1 - 4 of 4
Results Per Page
Sort Options
- Evolutionary Swarm based algorithms to minimise the link cost in Communication NetworksPublication . Moreira Bernardino, Anabela; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel Ángel; Bernardino, Eugénia MoreiraIn the last decades, nature-inspired algorithms have been widely used to solve complex combinatorial optimisation problems. Among them, Evolutionary Algorithms (EAs) and Swarm Intelligence (SI) algorithms have been extensively employed as search and optimisation tools in various problem domains. Evolutionary and Swarm Intelligent algorithms are Artificial Intelligence (AI) techniques, inspired by natural evolution and adaptation. This paper presents two new nature-inspired algorithms, which use concepts of EAs and SI. The combination of EAs and SI algorithms can unify the fast speed of EAs to find global solutions and the good precision of SI algorithms to find good solutions using the feedback information. The proposed algorithms are applied to a complex NP-hard optimisation problem - the Terminal Assignment Problem (TAP). The objective is to minimise the link cost to form a network. The proposed algorithms are compared with several EAs and SI algorithms from literature. We show that the proposed algorithms are suitable for solving very large scaled problems in short computational times.
- Hybrid population-based incremental learning to assign terminals to concentratorsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelIn the last decade, we have seen a significant growth in communication networks. In centralised communication networks, a central computer serves several terminals or workstations. In large networks, some concentrators are used to increase the network efficiency. A collection of terminals is connected to a concentrator and each concentrator is connected to the central computer. In this paper we propose a Hybrid Population-based Incremental Learning (HPBIL) to assign terminals to concentrators. We use this algorithm to determine the minimum cost to form a network by connecting a given collection of terminals to a given collection of concentrators. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.
- A Hybrid Scatter Search algorithm to assign terminals to concentratorsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelThe last few years have seen a significant growth in communication networks. With the growth of data traffic, network operators seek network-engineering tools to extract the maximum benefits out of the existing infrastructure. This has suggested a number of new optimisation problems, most of them in the field of combinatorial optimisation. We address here the Terminal Assignment problem. The main objective is to assign a collection of terminals to a collection of concentrators. In this paper, we propose a Hybrid Scatter Search (HSS) algorithm to assign terminals to concentrators. Coupled with the Scatter Search algorithm we use a Tabu Search algorithm to locate the global minimum. We show that HSS is able to achieve feasible solutions to Terminal Assignment instances, improving the results obtained by previous approaches.
- Solving the ring arc-loading problem using a hybrid scatter search algorithmPublication . Bernardino, Anabela Moreira; Bernardino, Eugénia Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelResilient Packet Ring (RPR) is a standard that uses Ethernet switching and a dual counter-rotating ring topology to provide SONET-like network resiliency and optimised bandwidth usage, while it delivers multipoint Ethernet/IP services. An important optimisation problem arising in this context is the Weighted Ring Arc Loading Problem (WRALP). That is the design of a direct path for each request in a communication network, in such a way that high load on the arcs will be avoided, where an arc is an edge endowed with a direction. The load of an arc is defined as the total weight of those requests routed through the arc in its direction. WRALP ask for a routing scheme such that the maximum load on the arcs will be minimum. In this paper we study the loading problem without demand splitting and for solving it we propose a Hybrid Scatter Search (HSS) algorithm. Coupled with the Scatter Search algorithm we use a Tabu Search algorithm to locate the global minimum. We show that HSS is able to achieve feasible solutions to WRALP instances, improving the results obtained by previous approaches.