## About

61

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166

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Citations since 2017

Introduction

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February 2008 - present

## Publications

Publications (61)

The One-Dimensional Cutting Stock Problem with Setup Cost (CSP-S) is a cutting problem that seeks a cutting plan with a minimum number of objects and a minimum number of different patterns. This problem gains relevance in manufacturing settings, where time consuming operations to set up the knives of the cutting machine for the new patterns increas...

3D protein structures and nanostructures can be obtained by exploiting distance information provided by experimental techniques, such as nuclear magnetic resonance and the pair distribution function method. These are examples of instances of the unassigned distance geometry problem (uDGP), where the aim is to calculate the position of some points u...

This paper proposes a new paradigm for solving robust optimization problems using sampling within a multi-objective framework to solve the Bandwidth Packing Problem, the Sampling-based Robust Optimization Method (SIROM). The key feature of this new approach is that it performs robust optimization without having to specify a priori an uncertainty bu...

In this paper, we present the online tool http://salaplanejada.unifesp.br, developed to assist the layout planning of classrooms considering the social distancing in the context of the COVID-19 pandemic. We address both the fixed and non-fixed position seat allocation problems. For the first case, we use two integer optimization models and discuss...

A Golomb Ruler (GR) is a set of integer marks along an imaginary ruler such that all the distances of the marks are different. Computing a GR of minimum length is associated to many applications (from astronomy to information theory). Although not yet demonstrated to be NP-hard, the problem is computationally very challenging. This brief note propo...

In this paper, we present the online tool salaplanejada.unifesp.br developed to assist the layout planning of classrooms considering the social distance in the context of the COVID-19 pandemic. We address both the allocation problem in rooms where seats are fixed as well as the problem in rooms where seats can be moved freely. For the first case, w...

Using information from protein geometry and distance data provided by Nuclear Magnetic Resonance (NMR) experiments, the Molecular Distance Geometry Problem (MDGP) can be solved by a combinatorial approach, called Branch-and-Prune (BP). The primal version of BP algorithm seeks MDGP graph realizations, while the dual BP looks for completions of assoc...

This chapter, some of whose ideas we have taken from [1–3], develops flexible and generalized uncertainty optimization where the salient feature of the problem is decision making under gradual set belonging. As we have mentioned in Chap. 1, optimization problems are normative processes that embody the idea of order since we must measure how one out...

This chapter focuses on generalized uncertainty optimization. Specifically, we develop in more detail four types of generalized uncertainty optimization, two of historical significance, Tanaka, Asai, Ichihashi [1, 2] Buckley [3, 4], and two newer ways due to Jamison, Lodwick, Thipwiwatpotjana [5–8] and a completely new presentation of generalized u...

Chapter 1 introduced the topics of interest to this monograph. Chapter 2 briefly looked at the underlying theory behind the data input types—flexible/fuzzy entities and generalized uncertainty entities: intervals, fuzzy intervals, possibility pairs, interval-valued probabilities, cumulative probability bounds (P-Boxes), clouds, Kolmogorov–Smirnov b...

This chapter focuses on the various theories of generalized uncertainty that occur in the data associated with optimization models under generalized uncertainty. Fuzzy set theory as it is applied to optimization is quite well-developed and a distinct study with many textbooks [1, 2] as well as an associated journal, Fuzzy Optimization and Decision...

This introductory chapter looks at the wide array of results in the area of flexible and generalized uncertainty which includes fuzzy optimization, and possibility optimization.

This chapter focuses on flexible optimization. Given that we are able to construct fuzzy relations from target values, fuzzy goals, and from fuzzy relation membership functions, we then have a fuzzy constraint set. The next step in the process is to translate a fuzzy constraint set into a real vector constraint set and to redefine the objective fun...

This book presents the theory and methods of flexible and generalized uncertainty optimization. Particularly, it describes the theory of generalized uncertainty in the context of optimization modeling. The book starts with an overview of flexible and generalized uncertainty optimization. It covers uncertainties that are both associated with lack of...

ABSTRACT Maritime shipping is vital to worldwide commerce. Due to the high flow in ports throughout the world, the efficient allocation of vessels in berths has become a problem. A new mathematical model and several algorithms are proposed in this paper to planning the allocation of the vessels in berths and the allocation of resources to the servi...

In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts o...

Frente à necessidade de gerenciamento e previsão do número de leitos de unidades de terapia intensiva (UTI) para pacientes graves de covid-19, foi desenvolvido o Forecast UTI, um aplicativo de livre acesso e que permite o monitoramento de indicadores hospitalares com base em dados históricos do serviço de saúde e na dinâmica temporal dessa epidemia...

This paper presents a new approach to the generalized distance geometry problem, based on a model that uses constraint interval arithmetic. In addition to theoretical results, we give some computational experiments that illustrate the better performance of the proposed approach, compared to others from the literature.

Resumo Frente à necessidade de gerenciamento e previsão do número de leitos de unidades de terapia intensiva (UTIs) para pacientes graves de COVID-19, foi desenvolvido o Forecast UTI, um aplicativo de livre acesso, que permite o monitoramento de indicadores hospitalares com base em dados históricos do serviço de saúde e na dinâmica temporal da epid...

The operational efficiency of a port depends on proper container movement planning, called “stowage planning”, especially because unloading and loading container ships demands time, and this has a cost. Thus, the optimization of operations through stages is important to avoid blockage activities. This paper proposes a framework for solving the 3D s...

This work presents a sufficient criteria for partial efficient solutions of the cutting stock problem with two objectives. We consider two important objectives for an industry: number of processed objects (cost of raw materials) and number of different patterns (cost of setup). These optimality results are established through a new approach based o...

In this work we propose a heuristic algorithm for the layout optimization for disks installed in a rotating circular container. This is a unequal circle packing problem with additional balance constraints. It proved to be an NP-hard problem, which justifies heuristics methods for its resolution in larger instances. The main feature of our heuristic...

The 3D Container ship Loading Plan Problem (CLPP) is an important problem that appears in seaport container terminal operations. This problem consists of determining how to organize the containers in a ship in order to minimize the number of movements necessary to load and unload the container ship and the instability of the ship in each port. The...

Nos ultimos anos a industria ﬁnanceira no Brasil e no mundo vem se modernizando tendo em vista a utilizacao de tecnicas matematicas mais robustas e soﬁsticadas no momento da tomada de decisoes estrategicas. Uma decisao estrategica muito comum nas instituicoes ﬁnanceiras e a alocacao otima dos ativos ﬁnanceiros. Em geral, este problema consiste em a...

Resumo: Nesse artigo foram utilizados seis conjuntos de ações de empresas de aviação negociadas na bolsa de valores de Nova Iorque (NYSE). As empresas selecionadas arbitrariamente tiveram como objetivo compor uma carteira setorial para aplicação do modelo Black-Litterman. As vantagens dessa aplicação são a superação da sensibilidade das mudanças no...

In this work we propose a heuristic algorithm for the layout optimization for
disks installed in a rotating circular container. This is a unequal circle
packing problem with additional balance constraints. It proved to be an NP-hard
problem, which justifies heuristic methods for its resolution. The main feature
of our heuristic is based on the sele...

This paper formulates the 3D Stochastic Stowage Plan-ning (3D SSP) problem. The key objective of 3D SSP is to minimize the number of container movements and maximize the ship´s stability considering multiple scenar-ios. The binary formulation of this problem is described and an alternative formulation, called Representation by Rules, is combined wi...

Edilson Fernandes de Arruda (UFRJ) efarruda@pep.ufrj.br Luiz Leduino Salles Neto (UNIFESP) luiz.leduino@unifesp.br Antônio Augusto Chaves (UNIFESP) antonio.chaves@unifesp.br Antônio Carlos Moretti (UNICAMP) moretti@ime.unicamp.br Resumo:Neste artigo é apresentada uma nova forma de resolução do problema de carregamento de contêineres 3D em terminais...

This paper presents the application of the one new approach using Genetic Algorithm in solving One-Dimensional Cutting Stock Problems in order to minimize two objectives, usually conflicting, i.e., the number of processed objects and setup while simultaneously treating them as a single goal. The model problem, the objective function, the method den...

This study presents the promising results obtained for an intelligent decision-making system for industrial processes in which the cutting stock problem is a component relevant to production planning. In order to establish a cutting process assisted by an intelligent system, with memory and learning capabilities, we utilised a symbiotic genetic alg...

This paper formulates the 3D Container ship Loading Planning Problem (3D CLPP) and also proposes a new and compact representation to efficiently solve it. Containers on board a Container ship are placed in vertical stacks, located in different sections. The only way to access the containers is through the top of the stack. In order to unload a cont...

This paper presents the application of the one new approach using Genetic Algorithm in solving One-Dimensional Cutting Stock Problems in order to minimize two objectives, usually conflicting, i.e., the number of processed objects and setup while simultaneously treating them as a single goal. The model problem, the objective function, the method den...

In this work, we introduce a new method to minimize the number of processed objects and the setup number in a unidimensional cutting stock problem. A nonlinear integer programming problem can be used to represent the problem studied here. The term related to the minimization of the setup number is a nonlinear discontinuous function, we smooth it an...

In this chapter we present and prove different forms of weak, strong and converse duality theorems for the Wolfe and Mond-Weir dual problems associated with the vector optimization problem with constraints, where the vector objective function and the vector function associated with the inequality-type constraints are invex, strictly invex or quasi-...

This work presents a genetic symbiotic algorithm to minimize the number of objects and the setup in a one-dimensional cutting stock problem. The algorithm implemented can generate combinations of ordered lengths of stock (the cutting pattern) and, at the same time, the frequency of the cutting patterns, through a symbiotic process between two disti...

This work presents a genetic symbiotic algorithm to solve the one-dimensional cutting stock problem with multiple objectives. We considered two important objectives for an industry (1) cost of trim loss and (2) cost of setup. We use a symbiotic relationship, between the population of solutions and the population of cutting patterns, together with a...

RESUMEN Este estudio presenta un nuevo modelo matemático y un procedimiento metaheurístico de búsqueda voraz adaptativa y aleatoria (GRASP, por sus siglas en inglés) para resolver el problema de stock de corte ordenado. Este problema ha sido introducido recientemente en la literatura. Es apropiado minimizar la materia prima usada por las industrias...

In this article we solve a nonlinear cutting stock problem which represents a cutting stock problem that considers the minimization of, both, the number of objects used and setup. We use a linearization of the nonlinear objective function to make possible the generation of good columns with the Gilmore and Gomory procedure. Each time a new column i...

This study presents a new mathematical model a Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic to solve the ordered cutting stock problem. The ordered cutting stock problem was recently introduced in literature. It is appropriate to minimize the raw material used by industries that deal with reduced product inventories, such as in...

In this article we solve a nonlinear cutting stock problem which represents a cutting stock problem that considers the minimization of, both, the number of objects used and setup. We use a linearization of the nonlinear objective function to make possible the generation of good columns with the Gilmore and Gomory procedure. Each time a new column i...

2 Abstract. In this work we introduce a new method to minimize the number 3 of processed objects and the setup number in a unidimensional cutting 4 stock problem. A nonlinear integer programming problem can be used to 5 represent the problem studied here. The term related to the minimization 6 of the setup number is a nonlinear discontinuous functi...

In this work we studied the NP-hard combinatorial nonidentical circle packing prob-lem. It consists of packing a set of circles of different radius dimensions into a circular region taking in account the design and technological considerations. Our problem is a little bit dif-ferent, we want to place a circular weighted objects inside a circular co...

Multiobjective combinatorial optimization has not been studied widely and very few theoretical results are available, in particular for cutting stock problems. In this work, we present our current developments in the study of conditions for weakly efficient solutions of one-dimensional cutting stock problem with multiple objectives. We consider the...

Bioinspired optimization algorithms, such as genetic algorithms and particle swarms, have been used to solve the problem of allocation of cylinders in a circular container. When the height of the cylinders is not considered, the problem is reduced to the allocation of circles, each one with a mass value. This article presents an implementation of t...

In this work we introduce a new method to minimize the number of processed objects and the setup number in a unidimensional cutting stock problem. A nonlinear integer programming problem can be used to represent the problem studied here. The term related to the minimization of the setup number is a nonlinear discontinuous function, we smooth it and...

## Projects

Project (1)

The operational efficiency of a port depends on a proper container moving planning. This includes a proper ship container arrangement planning through ports known as "stowage planning" and port equipment coordination that allows the container ship loading and unloading cargo from and to yard by using quay cranes, vehicles and, gantry cranes or straddle carrier. This project proposes a study on simulation and mathematical formulations to develop a framework for solving and integrate the five main problems that appears on Port Operation: Berth Allocation, Stowage Planning, Crane Split, Quayside transport and Land-side transport. Each problem is itself a combinatorial one which justifies the applications of meta-heuristics. Another drawback for real problems is related to solution encoding, which mathematical models demands a large number of binary variables to represent a solution. For example, a Stowage Planning solution that produces a complete stowage plan through 30 ports and a container ship size of 1500 TEUs will demand 40,545,000 binary variables to represent just one solution. This justifies not only the use of heuristics for problems, but also a different way to represent the solution. The robustness of the developed approach will be attested in problems with real size dimensions and will emphasize the integration of operations through port.