N. Maculan - Academia.edu (original) (raw)

Papers by N. Maculan

In this paper, constraint and integer programming formulations are applied to solve Bandwidth Col... more In this paper, constraint and integer programming formulations are applied to solve Bandwidth Coloring Problem (BCP) and Bandwidth Multicoloring Problem (BMCP). The problems are modeled using distance geometry (DG) approaches, which are then used to construct the constraint programming formulation. The integer programming formulation is based on a previous formulation for the related Minimum Span Frequency Assignment Problem (MSFAP), which is modified in order to reduce its size and computation time. The two exact approaches are implemented with available solvers and applied to well-known sets of instances from the literature, GEOM and Philadelphia-like problems. Using these models, some heuristic solutions from previous works are proven to be optimal, a new upper bound for an instance is given and all optimal solutions for the Philadelphia-like problems are presented. A discussion is also made on the performance of constraint and integer programming for each considered coloring pro...

RAIRO - Operations Research, 2003

We present an exact method for integer linear programming problems that combines branch and bound... more We present an exact method for integer linear programming problems that combines branch and bound with column generation at each node of the search tree. For the case of models involving binary column vectors only, we propose the use of so-called geometrical cuts to be added to the subproblem in order to eliminate previously generated columns. This scheme could be applied to general integer problems without specific structure. We report computational results on a successful application of this approach to a telecommunications network planning problem.

Anais do Encontro de Teoria da Computação (ETC), 2018

Neste trabalho, apresenta-se o modelo baseado em distâncias para o problema clássico de coloração... more Neste trabalho, apresenta-se o modelo baseado em distâncias para o problema clássico de coloração de vértices em grafos (VCP). A formulação de programação linear inteira utiliza variáveis de decisão que representam a distância entre cores atribuídas para cada par de vértices distintos, no lugar de fornecer explicitamente tais cores. Mostra-se que há uma relação próxima entre esta formulação e o modelo baseado em orientação para o VCP, proposto também pelos autores deste trabalho. Em particular, prova-se que desigualdades indutoras de facetas para o modelo baseado em orientação podem ser traduzidas em desigualdades indutoras de facetas para o modelo baseado em distâncias e vice-versa.

International Transactions in Operational Research, 2019

One of the most important classes of combinatorial optimization problems is graph coloring, and t... more One of the most important classes of combinatorial optimization problems is graph coloring, and there are several variations of this general problem involving additional constraints either on vertices or edges. They constitute models for real applications, such as channel assignment in mobile wireless networks. In this work, we consider some coloring problems involving distance constraints as weighted edges, modeling them as distance geometry problems (DGPs). Thus, the vertices of the graph are considered as embedded on the real line and the coloring is treated as an assignment of positive integers to the vertices, while the distances correspond to line segments, where the goal is to find their feasible intersection. We formulate these coloring problem variants and show feasibility conditions for some problems. We also propose implicit enumeration methods for some of the optimization problems based on branch-and-prune algorithms proposed for DGPs in the literature. An empirical analysis was undertaken, considering equality and inequality constraints, and uniform and arbitrary set of distances. As the main contributions, we propose new variations of vertex coloring problems in graphs, involving a new theoretical model in distance geometry (DG) for vertex coloring problems with generalized adjacency constraints, promoting the correlation between graph theory and DG fields. We also give a characterization and formal proof of polynomial cases for special graph classes, since the general main problem is NP-complete.

ArXiv, 2016

One of the most important combinatorial optimization problems is graph coloring. There are severa... more One of the most important combinatorial optimization problems is graph coloring. There are several variations of this problem involving additional constraints either on vertices or edges. They constitute models for real applications, such as channel assignment in mobile wireless networks. In this work, we consider some coloring problems involving distance constraints as weighted edges, modeling them as distance geometry problems. Thus, the vertices of the graph are considered as embedded on the real line and the coloring is treated as an assignment of positive integers to the vertices, while the distances correspond to line segments, where the goal is to find a feasible intersection of them. We formulate different such coloring problems and show feasibility conditions for some problems. We also propose implicit enumeration methods for some of the optimization problems based on branch-and-prune methods proposed for distance geometry problems in the literature. An empirical analysis w...

European Journal of Operational Research, 2015

We propose a new speed and departure time optimization algorithm for the Pollution-Routing Proble... more We propose a new speed and departure time optimization algorithm for the Pollution-Routing Problem (PRP), which runs in quadratic time and returns a certified optimal schedule. This algorithm is embedded into an iterated local search-based metaheuristic to achieve a combined speed, scheduling and routing optimization. The start of the working day is set as a decision variable for individual routes, thus enabling a better assignment of human resources to required demands. Some routes that were evaluated as unprofitable can now appear as viable candidates later in the day, leading to a larger search space and further opportunities of distance optimization via better service consolidation. Extensive computational experiments on available PRP benchmark instances demonstrate the good performance of the algorithms. The flexible departure times from the depot contribute to reduce the operational costs by 8.36% on the considered instances.

Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks, 2000

Page 1. A hybrid genetic algorithm for finding stable conformations of small molecules HJC Barbos... more Page 1. A hybrid genetic algorithm for finding stable conformations of small molecules HJC Barbosa and FMP Raupp Laboratbrio Nacional de Computa@o Cientifica ... D. Whitley, Morgan Kaufmann, San Mateo, CA (1993), pp. 187-202. ...

International Transactions in Operational Research, 2010

Stratified sampling is a technique that consists in separating the elements of a population into ... more Stratified sampling is a technique that consists in separating the elements of a population into nonoverlapping groups, called strata. This paper describes a new algorithm to solve the one-dimensional case, which reduces the stratification problem to just determining strata boundaries. Assuming that the number L of strata and the total sample size n are predetermined, we obtain the strata boundaries by taking into consideration an objective function associated with the variance. In order to solve this problem, we have implemented an algorithm based on the iterative local search metaheuristic. Computational results obtained from a real data set are presented and discussed.

1 Systems Engineering and Computer Science Program UFRJ Rio de Janeiro, Brazil 2 Institute of... more 1 Systems Engineering and Computer Science Program UFRJ Rio de Janeiro, Brazil 2 Institute of Computing University of Campinas, Campinas, Brazil 3 Department of Informatics PUC-Rio Rio de Janeiro, Brazil ... This paper introduces the Brazilian Institute for ...

RAIRO - Operations Research, 1997

Revue française d'automatique, d'informatique et de recherche opérationnelle. Recherche opération... more Revue française d'automatique, d'informatique et de recherche opérationnelle. Recherche opérationnelle, tome 31, n o 4 (1997), p. 331-341. <http://www.numdam.org/item?id=RO_1997__31_4_331_0> © AFCET, 1997, tous droits réservés. L'accès aux archives de la revue « Revue française d'automatique, d'informatique et de recherche opérationnelle. Recherche opérationnelle » implique l'accord avec les conditions générales d'utilisation (http://www.numdam.org/ legal.php). Toute utilisation commerciale ou impression systématique est constitutive d'une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright. Article numérisé dans le cadre du programme Numérisation de documents anciens mathématiques http://www.numdam.org/ Recherche opérationnelle/Opérations Research (vol. 31, n° 4, 1997, pp. 331 à 341) A TRUST REGION METHOD FOR ZERO-ONE NONLINEAR PROGRAMMING (*) by D. MAURICIO (l) and N. MACULAN (2) Coramunicated by Pierre TOLLA Abstract.-An Ö (n log n) trust région approximation method to solve 0-1 non-linearprogramming is présentée. Optimality conditions and numerical resulîs are reported.

Pesquisa Operacional, 2000

In this work we present an enumerative scheme for determining the K-best solutions (K > 1) of ... more In this work we present an enumerative scheme for determining the K-best solutions (K > 1) of the one dimensional knapsack problem. If n is the total number of different items and b is the knapsack's capacity, the computational complexity of the proposed scheme is bounded by O(Knb) with memory requirements bounded by O(nb). The algorithm was implemented in a workstation and computational tests for varying values of the parameters were performed.

IEEE Latin America Transactions, 2010

The Compartmentalized Knapsack Problem has been reported in the literature to generate cutting pa... more The Compartmentalized Knapsack Problem has been reported in the literature to generate cutting patterns of problems in two stages. The problem has constrained case, which are considered limits on the number of compartments and items in the knapsack. An exact algorithm that involves the resolution of various knapsacks and heuristics based on upper bound has already been developed. In this paper we present the problem with mathematical models and propose new strategies for resolving the constrained case.

Computational Optimization and Applications, 2004

The expansion of telecommunication services has increased the number of users sharing network res... more The expansion of telecommunication services has increased the number of users sharing network resources. When a given service is highly demanded, some demands may be unmet due to the limited capacity of the network links. Moreover, for such demands, telecommunication operators should pay penalty costs. To avoid rejecting demands, we can install more capacities in the existing network. In this paper we report experiments on the network capacity design for uncertain demand in telecommunication networks with integer link capacities. We use Poisson demands with bandwidths given by normal or log-normal distribution functions. The expectation function is evaluated using a predetermined set of realizations of the random parameter. We model this problem as a two-stage mixed integer program, which is solved using a stochastic subgradient procedure, the Barahona's volume approach and the Benders decomposition.

We consider the Multiprocessor Scheduling Problem with Communication Delays, where the delay is p... more We consider the Multiprocessor Scheduling Problem with Communication Delays, where the delay is proportional to both the amount of exchanged data between pairs of dependent tasks and the distance between processors in the multiprocessor architecture. Although scheduling problems are usually solved by means of heuristics due to their large sizes, we propose methods to identify optimal solutions of small and medium-scale instances. A set of instances with known optima is a useful benchmarking tool for new heuristic algorithms. We propose two new Mixed-Integer Bilinear Programming formulations, we linearize them in two different ways, and test them with CPLEX 8.1. To decrease the time needed by CPLEX for finding the optimal solution, we use Variable Neighborhood Search heuristic to obtain a good approximation for the initial solution.

International Transactions in Operational Research, 2009

In this paper, we are interested in the shortest path problem between two specified vertices in d... more In this paper, we are interested in the shortest path problem between two specified vertices in digraphs containing negative cycles. We study two integer linear formulations and their linear relaxations. A first formulation, close in spirit to a classical formulation of the traveling salesman problem, requires an exponential number of constraints. We study a second formulation that requires a polynomial number of constraints and, as confirmed by computational experiments, its linear relaxation is significantly sharper. From the second formulation we propose a family of linear relaxations with fewer variables than the classical linear one.

IEEE Latin America Transactions

This paper presents a strategy to design a Demand Side Management in the Brazilian energy market,... more This paper presents a strategy to design a Demand Side Management in the Brazilian energy market, using stochastic optimization and price elasticity of demand. This paper evaluates the proxy value for triggering the Incentive-based program of Demand Response (DR) in a Brazilian utility company. Then, the results show the proxy values for three types of customers, regarding the deficit scenarios. Also, the Value of Stochastic Solution proves the impact of the cost of ignoring uncertainty in designing this DR program.