Este artigo apresenta um algoritmo memético aplicado ao TSP Assimétrico, trazendo a proposta de u... more Este artigo apresenta um algoritmo memético aplicado ao TSP Assimétrico, trazendo a proposta de uma nova busca local, denominada Recursive Edge Inseetion (REI). A população é estruturada hierarquic...
We advance the state of the art in Mixed-Integer Linear Programming formulations for Guillotine 2... more We advance the state of the art in Mixed-Integer Linear Programming formulations for Guillotine 2D Cutting Problems by (i) adapting a previously-known reduction to our preprocessing phase (plate-size normalization) and by (ii) enhancing a previous formulation (PP-G2KP from Furini et alli) by cutting down its size and symmetries. Our focus is the Guillotine 2D Knapsack Problem with orthogonal and unrestricted cuts, constrained demand, unlimited stages, and no rotation – however, the formulation may be adapted to many related problems. The code is available. Concerning the set of 59 instances used to benchmark the original formulation, the enhanced formulation takes about 4 hours to solve all instances while the original formulation takes 12 hours to solve 53 of them (the other six runs hit a three-hour time limit each). We integrate, to both formulations, a pricing framework proposed for the original formulation; the enhanced formulation keeps a significant advantage in this situatio...
We study the effect of perturbations on the Price of Anarchy for the Traffic Assignment Problem. ... more We study the effect of perturbations on the Price of Anarchy for the Traffic Assignment Problem. Adopting the smoothed analysis approach, we randomly perturb the latency functions of the given network and estimate the expected Price of Anarchy on the perturbed instances. We provide both theoretical and experimental results that show that the Smoothed Price of Anarchy is of the same order of magnitude as the original one.
This work presents two data stream algorithms for wireless sensor networks (WSNs), based in sam... more This work presents two data stream algorithms for wireless sensor networks (WSNs), based in sample and sketch technics. For each case, we show that by using our algorithms, we can save energy and reduce delay in WSN applications in different scenarios. Speci cally, the sampling solution, provides a sample of only log n items to represent the original data of n elements. Despite of reduction, the sampling solution keep a good data quality.
The Internet is divided into Autonomous Systems, which cont rol their intra-domain traffic by usi... more The Internet is divided into Autonomous Systems, which cont rol their intra-domain traffic by using interior gateway protocols. The most common protocol used today is Open Shortest Path First (OSPF). OSPF routes traffic on shortest paths defined by integer link weights. The weight setting problem is to find weights that optimize the resultin g raffic, for example to minimize network congestion. A recently proposed protocol called Distribut ed Exponentially-weighted Flow Splitting (DEFT) sends flow on non-shortest paths, with an exponential penalty for longer paths. Since these problems are hard to solve exactly, several heuristics have been proposed. We propose a parallel, multi-deme version of a memetic algorithm to solve the weigh t setting problem in DEFT. It consists of a shared memory parallelization of the (single deme) meme tic algorithm, as well as instances of the memetic algorithm running in parallel, and migrating so luti ns among populations according to the island model...
We aim at provoking new ideas for computational tools based on the powerful algorithms currently ... more We aim at provoking new ideas for computational tools based on the powerful algorithms currently available for the TSP. They can help to order DNA sequences and can be viewed as complementary tools to the existing phylogenetic methods, uncovering interesting correlations not made explicit in most tree layouts. We study the problem of ordering the sequences such that they minimize the total intersequence distances. The distances are based on a measure that approximates Kolmogorov complexity. The method is fully automatizable, and the results are very encouraging.
The school timetabling is a classic optimization problem that takes a large number of variables a... more The school timetabling is a classic optimization problem that takes a large number of variables and constraints into account. Due to the combinatorial nature of this problem, it is very difficult to solve it manually and is often difficult to find a feasible solution when resources are tight. Among the different requirements that are considered in Brazilian Schools, two compactness requirements are essential on a teacher’s schedule: to minimize working days and to avoid idle times. In this work we explore the influence of four different idle times constraint formulations: two of them were previously proposed, and two are novel. Experimental results shown that a novel idle times constraint formulation produces better results for classical instances of the literature. One of these results is a new optimal solution and two of them are new best computed solutions. Finally, we also study the impact of double lessons and the minimization of working days in these formulations.
It's not surprisingly when entering this site to get the book. One of the popular books now i... more It's not surprisingly when entering this site to get the book. One of the popular books now is the network optimization. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And when you have found the store to buy the book, it will be so hurt when you run out of it. This is why, searching for this popular book in this website will give you benefit. You will not run out of this book.
The use of metaheuristics in Multi-objective Combinatorial Optimization, particularly Ant Colony ... more The use of metaheuristics in Multi-objective Combinatorial Optimization, particularly Ant Colony Optimization (ACO), has grown recently. This paper proposes an approach where multi-species ants compete for food resources. Each species has its own search strategy and do not access pheromone information of other species. As in nature, successful ant populations are allowed to grow, whereas the others shrink. This approach is applied to the Multi-objective Shortest Path Problem and shows to inherit the behavior of succesful strategies from different types of problems. It is also compared to an existing ACO and to NSGA-II. Results show that the proposed approach is able to produce significantly better approximation sets than other methods.
Este tutorial apresenta um metodo para geracao de instâncias de Problemas de Roteamento de Veicul... more Este tutorial apresenta um metodo para geracao de instâncias de Problemas de Roteamento de Veiculos com base em dados abertos. O objetivo principal e obter um processo automatizado e replicavel que permita a geracao de instâncias com caracteristicas proximas da realidade. O trabalho descreve um processo de obtencao de coordenadas geograficas dentro de uma area de interesse, bem como ferramentas a serem utilizadas para o calculo de distâncias e tempos de viagem respeitando a malha urbana local. Alem disso, apresenta metodos para a geracao de caracteristicas especificas do problema de roteamento para completar o processo de geracao de uma instância. Espera-se que este tutorial mostre como o uso de dados abertos pode ser usado para gerar instâncias que permitam novas analises de algoritmos de roteamento e o impacto que certas caracteristicas das instâncias tem neles e nas solucoes encontradas.
Este artigo apresenta um algoritmo memético aplicado ao TSP Assimétrico, trazendo a proposta de u... more Este artigo apresenta um algoritmo memético aplicado ao TSP Assimétrico, trazendo a proposta de uma nova busca local, denominada Recursive Edge Inseetion (REI). A população é estruturada hierarquic...
We advance the state of the art in Mixed-Integer Linear Programming formulations for Guillotine 2... more We advance the state of the art in Mixed-Integer Linear Programming formulations for Guillotine 2D Cutting Problems by (i) adapting a previously-known reduction to our preprocessing phase (plate-size normalization) and by (ii) enhancing a previous formulation (PP-G2KP from Furini et alli) by cutting down its size and symmetries. Our focus is the Guillotine 2D Knapsack Problem with orthogonal and unrestricted cuts, constrained demand, unlimited stages, and no rotation – however, the formulation may be adapted to many related problems. The code is available. Concerning the set of 59 instances used to benchmark the original formulation, the enhanced formulation takes about 4 hours to solve all instances while the original formulation takes 12 hours to solve 53 of them (the other six runs hit a three-hour time limit each). We integrate, to both formulations, a pricing framework proposed for the original formulation; the enhanced formulation keeps a significant advantage in this situatio...
We study the effect of perturbations on the Price of Anarchy for the Traffic Assignment Problem. ... more We study the effect of perturbations on the Price of Anarchy for the Traffic Assignment Problem. Adopting the smoothed analysis approach, we randomly perturb the latency functions of the given network and estimate the expected Price of Anarchy on the perturbed instances. We provide both theoretical and experimental results that show that the Smoothed Price of Anarchy is of the same order of magnitude as the original one.
This work presents two data stream algorithms for wireless sensor networks (WSNs), based in sam... more This work presents two data stream algorithms for wireless sensor networks (WSNs), based in sample and sketch technics. For each case, we show that by using our algorithms, we can save energy and reduce delay in WSN applications in different scenarios. Speci cally, the sampling solution, provides a sample of only log n items to represent the original data of n elements. Despite of reduction, the sampling solution keep a good data quality.
The Internet is divided into Autonomous Systems, which cont rol their intra-domain traffic by usi... more The Internet is divided into Autonomous Systems, which cont rol their intra-domain traffic by using interior gateway protocols. The most common protocol used today is Open Shortest Path First (OSPF). OSPF routes traffic on shortest paths defined by integer link weights. The weight setting problem is to find weights that optimize the resultin g raffic, for example to minimize network congestion. A recently proposed protocol called Distribut ed Exponentially-weighted Flow Splitting (DEFT) sends flow on non-shortest paths, with an exponential penalty for longer paths. Since these problems are hard to solve exactly, several heuristics have been proposed. We propose a parallel, multi-deme version of a memetic algorithm to solve the weigh t setting problem in DEFT. It consists of a shared memory parallelization of the (single deme) meme tic algorithm, as well as instances of the memetic algorithm running in parallel, and migrating so luti ns among populations according to the island model...
We aim at provoking new ideas for computational tools based on the powerful algorithms currently ... more We aim at provoking new ideas for computational tools based on the powerful algorithms currently available for the TSP. They can help to order DNA sequences and can be viewed as complementary tools to the existing phylogenetic methods, uncovering interesting correlations not made explicit in most tree layouts. We study the problem of ordering the sequences such that they minimize the total intersequence distances. The distances are based on a measure that approximates Kolmogorov complexity. The method is fully automatizable, and the results are very encouraging.
The school timetabling is a classic optimization problem that takes a large number of variables a... more The school timetabling is a classic optimization problem that takes a large number of variables and constraints into account. Due to the combinatorial nature of this problem, it is very difficult to solve it manually and is often difficult to find a feasible solution when resources are tight. Among the different requirements that are considered in Brazilian Schools, two compactness requirements are essential on a teacher’s schedule: to minimize working days and to avoid idle times. In this work we explore the influence of four different idle times constraint formulations: two of them were previously proposed, and two are novel. Experimental results shown that a novel idle times constraint formulation produces better results for classical instances of the literature. One of these results is a new optimal solution and two of them are new best computed solutions. Finally, we also study the impact of double lessons and the minimization of working days in these formulations.
It's not surprisingly when entering this site to get the book. One of the popular books now i... more It's not surprisingly when entering this site to get the book. One of the popular books now is the network optimization. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And when you have found the store to buy the book, it will be so hurt when you run out of it. This is why, searching for this popular book in this website will give you benefit. You will not run out of this book.
The use of metaheuristics in Multi-objective Combinatorial Optimization, particularly Ant Colony ... more The use of metaheuristics in Multi-objective Combinatorial Optimization, particularly Ant Colony Optimization (ACO), has grown recently. This paper proposes an approach where multi-species ants compete for food resources. Each species has its own search strategy and do not access pheromone information of other species. As in nature, successful ant populations are allowed to grow, whereas the others shrink. This approach is applied to the Multi-objective Shortest Path Problem and shows to inherit the behavior of succesful strategies from different types of problems. It is also compared to an existing ACO and to NSGA-II. Results show that the proposed approach is able to produce significantly better approximation sets than other methods.
Este tutorial apresenta um metodo para geracao de instâncias de Problemas de Roteamento de Veicul... more Este tutorial apresenta um metodo para geracao de instâncias de Problemas de Roteamento de Veiculos com base em dados abertos. O objetivo principal e obter um processo automatizado e replicavel que permita a geracao de instâncias com caracteristicas proximas da realidade. O trabalho descreve um processo de obtencao de coordenadas geograficas dentro de uma area de interesse, bem como ferramentas a serem utilizadas para o calculo de distâncias e tempos de viagem respeitando a malha urbana local. Alem disso, apresenta metodos para a geracao de caracteristicas especificas do problema de roteamento para completar o processo de geracao de uma instância. Espera-se que este tutorial mostre como o uso de dados abertos pode ser usado para gerar instâncias que permitam novas analises de algoritmos de roteamento e o impacto que certas caracteristicas das instâncias tem neles e nas solucoes encontradas.
Uploads
Papers by Luciana Buriol