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- CROSS-PLATFORM DEVELOPMENT FOR E-COMMERCEPublication . Vieira, Leandro; Bernardino, Anabela; Bernardino, EugéniaElectronic commerce is generally seen as a competitor for physical stores, however, this paper proposes a solution where they work side-by-side to improve the in-store customer experience. An application directed for store retailers was created with the cross-platform framework React Native, making it available for Android, iOS, and the web. Using thebe of their interest, and place orders, providing the customer with a unique and faster shopping experience.
- Solving the Ring Loading Problem Using Genetic Algorithms with Intelligent Multiple OperatorsPublication . Bernardino, Anabela M.; Bernardino, Eugénia M.; Sánchez-Pérez, Juan M.; Gómez-Pulido, Juan A.; Vega-Rodríguez, Miguel A.; Moreira Bernardino, Anabela; Bernardino, EugéniaPlanning optical communication networks suggests a number of new optimization problems, most of them in the field of combinatorial optimization. We address here the Ring Loading Problem. The objective of the problem is to find a routing scheme such that the maximum weighted load on the ring is minimized. In this paper we consider two variants: (i) demands can be split into two parts, and then each part is sent in a different direction; (ii) each demand must be entirely routed in either of the two directions, clockwise or counterclockwise. In this paper, we propose a genetic algorithm employing multiple crossover and mutation operators. Two sets of available crossover and mutation operators are established initially. In each generation a crossover method is selected for recombination and a mutation method is selected for mutation based on the amount fitness improvements achieve over a number of previous operations (recombinations/mutations). We use tournament selection for this purpose. Simulation results with the different methods implemented are compared.
- Solving the Terminal Assignment Problem Using a Local Search Genetic AlgorithmPublication . Bernardino, Eugénia M.; Bernardino, Anabela M.; Sánchez-Pérez, Juan M.; Gómez-Pulido, Juan A.; Vega-Rodríguez, Miguel A.; Bernardino, Eugénia; Moreira Bernardino, AnabelaTerminal assignment is an important issue in telecommunication networks optimization. The task here is to assign a given collection of terminals to a given collection of concentrators. The main objective is to minimize the link cost to form a network. This optimization task is an NP-complete problem. The intractability of this problem is a motivation for the pursuits of a local search genetic algorithm that produces approximate, rather than exact, solutions. In this paper, we explore one of the most successful emerging ideas combining local search with population-based search. Simulation results verify the effectiveness of the proposed method. The results show that our algorithm provides good solutions in a better running time.
- Billing in the Mobile Era : Octa Code’s Study CasePublication . Andrade, Eduardo; Bernardino, Anabela; Bernardino, EugeniaNa era digital, cada vez mais os serviços existentes se adaptam às novas tecnologias e aos seus benefícios. Com o surgimento de nova legislação, irá passar a ser obrigatório a utilização de plataformas digitas para todos os documentos de faturação. Com esta alteração, surge a necessidade de aplicações móveis que possam ser utilizadas em qualquer lado para substituir a tradicional fatura manual ainda utilizada em muitos negócios de cariz ambulante, onde o manuseamento de computadores ou portáteis não é fácil. Mas este novo mercado cria também novos desafios e problemas que serão explorados no caso de estudo em questão. Octa Gest Faturas, da Octa Code, é uma nova aplicação que pretende destacar-se ao oferecer uma experiência de fácil utilização, enquanto ao mesmo tempo aplica as práticas recomendadas no desenvolvimento de aplicações móveis.
- A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment ProblemPublication . Bernardino, Eugénia; Bernardino, Anabela; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelThe field of communication networks has witnessed tremendous growth in recent years resulting in a large variety of combinatorial optimization problems in the design and in the management of communication networks. One of these problems is the terminal assignment problem. The task here is to assign a given set of terminals to a given set of concentrators. In this paper, we propose a Hybrid Differential Evolution Algorithm to solve the terminal assignment problem. We compare our results with the results obtained by the classical Genetic Algorithm and the Tabu Search Algorithm, widely used in literature.
- Solving the non-split weighted ring arc-loading problem in a resilient packet ring using particle swarm optimizationPublication . Bernardino, Anabela; Bernardino, Eugénia; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelMassive growth of the Internet traffic in last decades has motivated the design of high-speed optical networks. Resilient Packet Ring (RPR), also known as IEEE 802.17, is a standard designed for the optimized transport of data traffic over optical fiber ring networks. Its design is to provide the resilience found in SONET/SDH networks but instead of setting up circuit oriented connections, providing a packet based transmission. This is to increase the efficiency of Ethernet and IP services. In this paper, a weighted ring arc-loading problem (WRALP) is considered which arises in engineering and planning of the RPR systems (combinatorial optimization NP- complete problem). Specifically, for a given set of non-split and uni-directional point-to-point demands (weights), the objective is to find the routing for each demand (i.e., assignment of the demand to either clockwise or counter-clockwise ring) so that the maximum arc load is minimized. This paper suggests four variants of Particle Swarm Optimization (PSO), combined with a Local Search (LS) method to efficient non-split traffic loading on the RPR. Numerical simulation results show the effectiveness and efficiency of the proposed methods.
- A hybrid ant colony optimization algorithm for solving the terminal assignment problemPublication . Bernardino, Eugénia; Bernardino, Anabela; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelThe past two decades have witnessed tremendous research activities in optimization methods for communication networks. One important problem in communication networks is the Terminal Assignment Problem. This problem involves determining minimum cost links to form a network by connecting a collection of terminals to a collection of concentrators. In this paper, we propose a Hybrid Ant Colony Optimization Algorithm to solve the Terminal Assignment Problem. We compare our results with the results obtained by the standard Genetic Algorithm, the Tabu Search Algorithm and the Hybrid Differential Evolution Algorithm, used in literature.
- Solving the weighted ring edge-loading problem without demand splitting using a Hybrid Differential Evolution AlgorithmPublication . Bernardino, Anabela; Bernardino, Eugénia; Sanchez-Perez, Juan Manuel; Gomez-Pulido, Juan Antonio; Vega-Rodriguez, Miguel AngelIn the last few years we have seen a significant growth in Synchronous Optical Network (SONET) deployments in telecommunication service providers. With 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 optimization problems, most of them in the field of combinatorial optimization. We address here the Weighted Ring Edge-Loading Problem (WRELP). The WRELP is an important optimization problem arising in a popular ring topology for communication networks - given a set of nodes connected along a bi-directional SONET ring, the objective is to minimize the maximum load on the edges (pairwise) of a ring. Our procedure includes some original features, including the application of Hybrid Differential Evolution. We also perform comparisons with standard Differential Evolution, Genetic Algorithm and Tabu Search.