Henrique Pacca Loureiro Luna

Benders Decomposition for Hub Location Problems with Economies of Scale

When considering hub-and-spoke networks with multiple allocation, the classical models of the literature compute solutions with large discount factors for small flows on interhub connections. Addressing the economies of scale issue, a tighter formulation for this problem is presented, bringing forward a special structure. A specialized version of Benders decomposition is then developed to solve large instances in reasonable time.

Multiple allocation hub-and-spoke network design under hub congestion

The multiple allocation hub-and-spoke network design under hub congestion problem is addressed in this paper. A non-linear mixed integer programming formulation is proposed, modeling the congestion as a convex cost function. A generalized Benders decomposition algorithm has been deployed and has successfully solved standard data set instances up to 81 nodes. The proposed algorithm has also outperformed a commercial leading edge non-linear integer programming package. The main contribution of this work is to establish a compromise between the transportation cost savings induced by the economies of scale exploitation and the costs associated with the congestion effects.

A transgenetic algorithm applied to the Traveling Car Renter Problem

The Traveling Car Renter is a new problem and constitutes a generalization of the Traveling Salesman. Several applications arise from it, mainly in the scheduling optimization of rental cars and in other problems concerning transport systems. In this paper, an integer quadratic programming model is presented for the Traveling Car Renter. It is linearized and implemented on a solver providing optimal solutions to a set of eighteen small instances. Large instances are tackled with a transgenetic algorithm proposed here. A computational experiment is reported on sixty instances and the proposed algorithm is compared to a memetic algorithm presented previously. The computational experiment aimed at focusing on the differences of performance between the two heuristic algorithms due to the search strategy used by each of them. Therefore, the implementation of both methods shared several elements. The results show that the transgenetic algorithm presents the best performance, indicating that its cooperative evolutionary process was more effective on the investigated problem than the competitive scheme of the memetic algorithm.

Global optimization of capacity expansion and flow assignment in multicommodity networks

This paper describes an exact algorithm to solve a nonlinear mixed-integer programming model due to capacity expansion and flow assignment in multicommodity networks. The model combines continuous multicommodity flow variables associated with nonlinear congestion costs and discrete decision variables associated with the arc expansion costs. After establishing precise correspondences between a mixed-integer model and a continuous but nonconvex model, an implicit enumeration approach is derived based on the convexification of the continuous objective function. Numerical experiments on medium size instances considering one level of expansion are presented. The results reported on the performance of the proposed algorithm show that the approach is efficient, as commercial solvers were not able to tackle the instances considered.

Quota traveling car renter problem

The quota traveling car renter problem is the quota variant of the traveling car renter problem. A graph is given where a bonus is associated with each vertex. The bonus is collected at every visited vertex. Several cars are available to travel the edges of the graph, each of which associates weights with the edges. The problem involves finding a cycle on a subset of vertices such that a predefined minimum sum of bonuses is obtained at least. The objective is to minimize the cost of the tour using the available cars. In this study, we propose an integer programming model for the problem, which is solved, and we present optimal solutions for 24 instances. We propose an evolutionary algorithm with a plasmid operator, which we compare with a memetic algorithm. We also present the results obtained based on computational experiments with 72 instances.

An ontology-based software framework to provide educational data mining

This paper presents an ontology-based software framework for providing educational data mining applications, mainly offering flexibility of encapsulate mining techniques with semantic web services. It consists of an architecture based on three layers. A case study and illustrative scenario have been implemented to evaluate the framework feasibility. Currently, the evaluation shows the pontential benefits for both the developer and the teacher.

Model and algorithms for the Multicommodity Traveling Salesman Problem

We are introducing in this article the Multicommodity Traveling Salesman Problem (MTSP), where the objective is to deliver all the demands of different commodities by a tour that minimizes the sum of the fixed and variable costs for the selected arcs. The MTSP yields then a large scale mixed integer linear programming problem. In this article we devise a Lagrangean based heuristic approach to tackle this more general TSP variant.

Network Planning Problems in Telecommunications

This chapter describes the main results of two decades of experience in studying and applying optimization models in the telecommunications sector. The Brazilian information technology policy has enabled during this time many fruitful contracts among some universities and companies of the sector, and the author with some colleagues have been engaged in this process with emphasis in the use of operations research (OR) methods. The author has also been benefited from the cooperation with French institutions that have similar engagements in that country, in such a way that the chapter is in part grounded in real case studies that have motivated research and development of different decision support systems. The chapter synthesize the framework that has been used to integrate models of local access and backbone networks, and then presents a past and future perspective on how is progressing the use of OR models to address the important questions of routing, planning and pricing services in telecommunication and computer networks. Most of the applications are related to the literature and have universal character, but we try to point out in this experience how different cultures, geography and politics impact and shape the way operations research is practiced around the world.

Um Framework para Mineração de Dados Educacionais Basedo em Serviçõs Semânticos

In the presence of the actual world context, the importance of knowing the technological resources and making use of them to improve the performance of human activities is realized. Educat ion cannot be laid aside of this reality, on the contrary, it has to be allied and seek for resources to improve even more the process of teaching and learn ing through Information and Communication Technologies (ICTs). Thus, the dof Araucaria/PR, through the Educational Technology Project, has pro vided access to these resources establishing informatics laboratories, ev aluating and reorganizing the used method, as an example, the accomplishment of the Leader-Teacher function related to the laboratory monitor one. Resumo. Diante do contexto do mundo atual, percebe-se a imp ortância de conhecer os recursos tecnologicos e fazer uso deste s para melhorar o desempenho das atividades humanas. A educacao nao pficar a margem desta realidade, ao contrario, deve buscar meios de aprimorar o processo de ensino e aprendizagem por meio das Tecnologias da I nformacao e Comunicacao (TICs). Assim, o municipio de Araucari a/PR, atraves do Projeto de Tecnologia Educacional, tem viabilizado o acesso a estes recursos com a implantacao de laboratorios de informatica, ae reorganizando os metodos empregados, como por exemplo, a implemen tacao da funcao de Professor-orientador em detrimento a funcao do moni tor de laboratorio.

Integer programming models and linearizations for the traveling car renter problem

The traveling car renter problem (CaRS) is an extension of the classical traveling salesman problem (TSP) where different cars are available for use during the salesman’s tour. In this study we present three integer programming formulations for CaRS, of which two have quadratic objective functions and the other has quadratic constraints. The first model with a quadratic objective function is grounded on the TSP interpreted as a special case of the quadratic assignment problem in which the assignment variables refer to visitation orders. The second model with a quadratic objective function is based on the Gavish and Grave’s formulation for the TSP. The model with quadratic constraints is based on the Dantzig–Fulkerson–Johnson’s formulation for the TSP. The formulations are linearized and implemented in two solvers. An experiment with 50 instances is reported.