Navegando por Autor "Carrano, Eduardo Gontijo"
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Item Feedback-control operators for improved Pareto-set description : application to a polymer extrusion process.(2015) Carrano, Eduardo Gontijo; Coelho, Dayanne Gouveia; Cunha, António Gaspar; Wanner, Elizabeth Fialho; Takahashi, Ricardo Hiroshi CaldeiraThis paper presents a new class of operators for multiobjective evolutionary algorithms that are inspired on feedback-control techniques. The proposed operators, the archive-set reduction and the surface-filling crossover, have the purpose of enhancing the quality of the description of the Pareto-set in multiobjective optimization problems. They act on the Pareto -estimate sample set, performing operations that eliminate archive points in the most crowded regions, and generate new points in the less populated regions, leading to a dynamic equilibrium that tends to generate a uniform sampling of the efficient solution set. The internal parameters of those operators are coordinated by feedback-control inspired techniques, which ensure that the desired equilibrium is attained. Numerical experiments in some benchmark problems and in a real problem of optimization of a single screw extrusion system for polymer processing show that the proposed methodology is able to generate more detailed descriptions of Pareto-optimal fronts than the ones produced by usual algorithms.Item Hybrid multicriteria algorithms applied to structural design of wireless local area networks.(2018) Lima, Marlon Paolo; Takahashi, Ricardo Hiroshi Caldeira; Vieira, Marcos Augusto Menezes; Carrano, Eduardo GontijoThis manuscript presents a novel approach based on hybrid optimization techniques for planning Wireless Local Area Networks in two stages: i) network structure design for access point (AP) placement and channel assignment and ii) channel assignment enhancement. We consider two objective functions: network load balance and signal-to-interference-plus-noise ratio; and three hard constraints: maximum AP capacities, client demand attendance, and minimum coverage levels. The proposed algorithm delivers an approximation of the efficient solution set, considering the two functions described above. The results from two scenarios were compared to the following four approaches: two multiobjective evolutionary algorithms, a well-known commercial tool, and a greedy technique. Finally, the solutions were subjected to sensitivity analysis to validate their robustness regarding user mobility and AP failures.Item Integer programming techniques for educational timetabling.(2017) Fonseca, George Henrique Godim da; Santos, Haroldo Gambini; Carrano, Eduardo Gontijo; Stidsen, Thomas Jacob RiisEducational timetabling problems require the assignment of times and resources to events, while sets of required and desirable constraints must be considered. The XHSTT format was adopted in this work because it models the main features of educational timetabling and it is the most used format in recent studies in the field. This work presents new cuts and reformulations for the existing integer programming model for XHSTT. The proposed cuts improved hugely the linear relaxation of the formulation, leading to an average gap reduction of 32%. Applied to XHSTT-2014 instance set, the alternative formulation pro- vided four new best known lower bounds and, used in a matheuristic framework, improved eleven best known solutions. The computational experiments also show that the resulting integer programming mod- els from the proposed formulation are more effectively solved for most of the instances.Item Integrating matheuristics and metaheuristics for timetabling.(2016) Fonseca, George Henrique Godim da; Santos, Haroldo Gambini; Carrano, Eduardo GontijoThe High School Timetabling Problem requires the assignment of times and resources to events, while sets of required and desirable constraints must be considered. The most common approach for this problem is to employ metaheuristic methods. This work presents a matheuristic approach that combines a Variable Neighbourhood Search algorithm with mathematical programming-based neighbourhoods for high school timetabling. Computational experiments on well-known benchmark instances demonstrate the success of the proposed hybrid approach, which outperforms the standalone Variable Neighbour- hood Search algorithm by far. Additionally, the proposed algorithm was able to improve 15 out of 17 current best known solutions in a very famous benchmark set.Item Late acceptance hill-climbing for high school timetabling.(2016) Fonseca, George Henrique Godim da; Santos, Haroldo Gambini; Carrano, Eduardo GontijoThe application of the Late Acceptance HillClimbing (LAHC) to solve the High School Timetabling Problem is the subject of this manuscript. The original algorithm and two variants proposed here are tested jointly with other state-of-art methods to solve the instances proposed in the Third International Timetabling Competition. Following the same rules of the competition, the LAHC-based algorithms noticeably outperformed the winning methods. These results, and reports from the literature, suggest that the LAHC is a reliable method that can compete with the most employed local search algorithms.Item Multiobjective planning of indoor Wireless Local Area Networks using subpermutation-based hybrid algorithms.(2023) Lima, Marlon Paolo; Takahashi, Ricardo Hiroshi Caldeira; Vieira, Marcos Augusto Menezes; Carrano, Eduardo GontijoWireless Local Area Network (WLAN) has become the most popular technology for mobile Internet access in recent decades. This manuscript presents a novel approach, based on hybrid optimization algorithms, for planning WLANs. Two objective functions are optimized: to maximize network load balance and signal-to-noise ratio. In addition, constraints related to coverage, customer, and equipment demand are considered. A key aspect of the proposed algorithm is its new representation/decoding scheme, based on subpermutations, which considerably reduces the search space dimension. This structure guarantees feasibility of the obtained solutions and increases the computational efficiency of the method. Several tests were performed in two scenarios, one of them using real data from a large-scale WLAN. When compared to other three approaches, such results show that the proposed method provides solutions that reduce costs and improve the WLAN throughput.Item On a vector space representation in genetic algorithms for sensor scheduling in wireless sensor networks.(2014) Martins, Flávio Vinícius Cruzeiro; Carrano, Eduardo Gontijo; Wanner, Elizabeth Fialho; Takahashi, Ricardo Hiroshi Caldeira; Mateus, Geraldo Robson; Nakamura, Fabiola GuerraRecent works raised the hypothesis that the assignment of a geometry to the decision variable space of a combinatorial problem could be useful both for providingmeaningful descriptions of the fitness landscape and for supporting the systematic construction of evolutionary operators (the geometric operators) that make a consistent usage of the space geometric properties in the search for problem optima. This paper introduces some new geometric operators that constitute the realization of searches along the combinatorial space versions of the geometric entities descent directions and subspaces. The new geometric operators are stated in the specific context of the wireless sensor network dynamic coverage and connectivity problem (WSN-DCCP). A genetic algorithm (GA) is developed for the WSN-DCCP using the proposed operators, being compared with a formulation based on integer linear programming (ILP) which is solved with exact methods. That ILP formulation adopts a proxy objective function based on the minimization of energy consumption in the network, in order to approximate the objective of network lifetime maximization, and a greedy approach for dealing with the system’s dynamics. To the authors’ knowledge, the proposed GA is the first algorithm to outperform the lifetime of networks as synthesized by the ILP formulation, also running in much smaller computational times for large instances.