Marcone J. F. Souza

Universidade Federal de Ouro Preto · Department of Computing

This work deals with the short-term planning problem of a work shift for open-pit mines. The problem involves ore and waste fronts, shovels, heterogeneous truck fleets, and discharge points. The allocation of trucks is dynamic to allow multiple routes to be assigned to each truck. The problem consists of deciding which fronts must be mined and esta...

Screening of Pap smear images continues to depend upon cytopathologists’ manual scrutiny, and the results are highly influenced by professional experience, leading to varying degrees of cell classification inaccuracies. In order to improve the quality of the Pap smear results, several efforts have been made to create software to automate and standa...

Data collection is the most important task in wireless sensor networks (WSN). Each sensor node has to send the sensed data to a special node called sink, which is the user interface. The sensor nodes far from the sink send data to intermediate nodes that forward it by multi-hop data paths. This characteristic leads to higher energy consumption in t...

This article addresses the Multi-Depot Vehicle Routing Problem with Time Windows with the minimization of the number of used vehicles, denominated as MDVRPTW*. This problem is a variant of the classical MDVRPTW, which only minimizes the total traveled distance. We developed an algorithm named Smart General Variable Neighborhood Search with Adaptive...

A análise de células cervicais a partir de exames de Papanicolaou convencionais ainda é um grande desafio. Diferentemente das imagens de exame em meio líquido, a citologia convencional possui muita sobreposição celular e diversas estruturas epiteliais que dificultam a implementação de metodologias computacionais que possam dar suporte à automação d...

In many countries, there is an energy pricing policy that varies according to the time-of-use. In this context, it is financially advantageous for the industries to plan their production considering this policy. This article introduces a new bi-objective unrelated parallel machine scheduling problem with sequence-dependent setup times, in which the...

This work proposes a bi-objective mathematical optimization model and a two-stage heuristic for a real-world application of the heterogeneous Dynamic Dial-a-Ride Problem with no rejects, i.e., a patient transportation system. The problem consists of calculating route plans to meet a set of transportation requests by using a given heterogeneous vehi...

This article presents a new mathematical formulation for the single allocation hub location problem with fixed cost and variable economies of scale and proposes the use of the metaheuristic Iterated Local Search (ILS), as a solution strategy. The hub location problems consist of determining the location of hubs in a connected network and establishi...

This article addresses a short-term mining planning problem. There are four objectives to be minimized: the deviations in grades and ore proportion in particle size ranges of the plant goals, the deviation in the waste mass to achieve the stripping rate, and the number of truck trips between mining fronts and discharges. The problem was solved thro...

This work addresses the multiple-depot vehicle and crew scheduling problem (MDVCSP). In MDVCSP, we deal with two NP-hard problems in an integrated way: the multiple-depot vehicle scheduling problem (MDVSP) and the crew scheduling problem (CSP). For solving the MDVCSP, we define the vehicles’ operational routine and the workdays of the crews of a pu...

A large amount of data available today and the complex situations present in the industry make decision support systems increasingly necessary. This work deals with a problem of a mining-metallurgical industry in which the production of products used to feed arc furnaces must be sequenced in work shifts. There is a due date and a quality specificat...

Feature selection is a widespread preprocessing step in the data mining field. One of its purposes is to reduce the number of original dataset features to improve a predictive model’s performance. Despite the benefits of feature selection for the classification task, as far as we are aware, few studies in the literature address feature selection fo...

O Problema das p-Medianas Capacitado (PPMC) consiste em localizar p facilidades em uma rede composta por n vértices e decidir qual facilidade atenderá cada vértice, a fim de minimizar a soma de todas as distâncias de cada facilidade para cada vértice e atenderàs restrições de capacidade máxima de cada facilidade. Neste trabalho, dado que o PPMC é d...

In recent years, deep learning methods have outperformed previous state-of-the-art machine learning techniques for several problems, including image classification. Classifying cells in Pap smear images is very challenging, and it is still of paramount importance for cytopathologists. The Pap test is a cervical cancer prevention test that tracks pr...

The Pap test is a preventive approach that requires specialized and labor-intensive examination of cytological preparations to track potentially cancerous cells from the internal and external cervix surface. A cytopathologist must analyze many microscopic fields while screening for abnormal cells. Therefore there is hope that a support decision sys...

In this paper, we propose a method to solve a bi-objective variant of the well-studied traveling thief problem (TTP). The TTP is a multi-component problem that combines two classic combinatorial problems: traveling salesman problem and knapsack problem. We address the BI-TTP, a bi-objective version of the TTP, where the goal is to minimize the over...

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-re...

This paper deals with the Green Electric Vehicle Routing Problem with Time Window and Mixed Fleet and presents a Mixed Integer Linear Programming formulation for it. Initially, we applied the CPLEX solver in this formulation. Then, to reduce the computational time, we used Local Branching and Variable Neighborhood Descent Branching (VNDB) methods....

As tecnologias de apoio à tomada de decisão vêm ganhando destaque na indústria mineral e metalúrgica, em que a procura por sustentabilidade, redução de custos e customização de produtos são cada vez mais necessárias. O sequenciamento de produtos representa uma parcela importante na eficiência dos processos industriais. Contudo, a abordagem manual d...

The benefits of using mobile sinks or data mules for data collection in Wireless Sensor Network (WSN) have been studied in several works. However, most of them consider only the WSN limitations and sensor nodes having no more than one data packet to transmit. This paper considers each sensor node having a relatively larger volume of data stored in...

In this paper, we introduce the double traveling salesman problem with partial last‐in‐first‐out loading constraints (DTSPPL). It is a pickup‐and‐delivery single‐vehicle routing problem, where all pickup operations must be performed before any delivery operation because the pickup‐and‐delivery areas are geographically separated. The vehicle collect...

The production rate of an ore crushing circuit depends on the amount of equipment in operation. If the amount of active equipment is less than the optimum level, the reduced ore flow paths restrict the production rate. However, if the amount of active equipment is greater than the optimum level, the excess circulating load ore and extra energy cons...

In this paper, we propose a simple heuristic algorithm based on the Variable Neighborhood Search (VNS), which combines with the Set Covering strategy in order to solve the Dial-a-Ride Problem (DARP). In this problem, customers must be served by a heterogeneous fleet of vehicles. Each customer has a pickup and a delivery location, where each one of...

This work deals with the mammography unit location problem in Brazil. In this problem, there is a set of mammography units to be installed in cities with hospital infrastructure and a set of cities, each with a demand for mammography screenings to be performed in women aged 40 to 69 years old. The goal is to decide where to install mammography unit...

The focus of this work is on the detection of nuclei in synthetic images of cervical cells. Finding nuclei is an important step in building a computational method to help cytopathologists identify cell changes from Pap smears. The method developed in this work combines both the Multi-Start and the Iterated Local Search metaheuristics and uses the f...

In this paper, we propose a method to solve a bi-objective variant of the well-studied Traveling Thief Problem (TTP). The TTP is a multi-component problem that combines two classic combinatorial problems: Traveling Salesman Problem (TSP) and Knapsack Problem (KP). In the TTP, a thief has to visit each city exactly once and can pick items throughout...

This work proposes a hybrid algorithm for the unrelated parallel machine scheduling problem with sequence-dependent setup times, aiming to minimize the makespan. The proposed algorithm, named Enhanced Smart General Variable Neighborhood Search (e-SGVNS), combines heuristic and exact optimization strategies to explore the solution space of the probl...

This special issue of the International Transactions in Operational Research focuses on Matheuristics and Metaheuristics and is the largest published to date, highlighting the importance of the field and the broad scope of these methods and the reach of their applications. Academicians and practitioners responded with enthusiasm to three parallel c...

Nem sempre a solução trivial de usar todos os equipamentos disponíveis em uma linha de produção é a solução de maior produtividade. Neste artigo, um algoritmo baseado em Simheuristic é aplicado em um sistema de suporte à decisão que busca a quantidade ótima de equipamentos que devem operar em um circuito de britagem. O estudo é feito com base em um...

Green machine scheduling consists in the allocation of jobs in order to maximize production, in view of the sustainable use of energy. This work addresses the unrelated parallel machine scheduling problem with setup times, with the minimization of the makespan and the total energy consumption. The latter takes into account the power consumption of...

RESUMO Este trabalho trata uma variação do problema de sequenciamento em máquinas paralelas não relacionadas com tempos de preparação dependentes da sequência, em que o objetivo é minimizar a soma ponderada dos valores normalizados do makespan e do custo total de energia. Neste problema há um conjunto de tarefas a serem executadas em um conjunto de...

RESUMO Este trabalho trata um problema de sequenciamento de tarefas em máquinas idênticas. No problema abordado, tem-se um conjunto de tarefas que devem ser alocadas a um conjunto de máquinas idênticas em um determinado instante de tempo, tendo como objetivo minimizar a soma ponderada do makespan e do consumo total de energia envolvido nessa operaç...

RESUMO Este trabalho trata do problema de localização de mamógrafos. Neste problema há um conjunto de cidades com demanda por exames de mamografia de sua população feminina e um conjunto de mamógrafos a serem instalados em um subconjunto dessas cidades. O objetivo é decidir onde instalar os mamógrafos de forma a maximizar a demanda total de exames,...

RESUMO Este trabalho apresenta um modelo de programação matemática por metas para resolver um problema de programação diária de lavra de uma mina de minério de ferro. O objetivo é minimizar os desvios das metas de produção e qualidade, bem como reduzir a quantidade de caminhões necessários ao processo. As restrições referentes a qualidade, granulom...

Este trabalho trata um problema de blendagem de pilhas intermediárias em uma mina de níquel. Aplicações de blendagem de minério são amplamente tratados na literatura, mas devido a especificidade das operações em uma mina de níquel, o problema deste estudo não foi encontrado. Nas minas de níquel é realizada estocagem em pilhas intermediárias de todo...

In this paper, we introduce the Double Traveling Salesman Problem with Partial Last-In-First-Out Loading Constraints (DTSPPL), a pickup-and-delivery single-vehicle routing problem where all pickup operations must be performed before any delivery one because the pickup and delivery areas are geographically separated. The vehicle collects items in th...

This paper addresses the single machine scheduling problem with distinct time windows, sequence-dependent setup times (SMSPETP) which consists in minimizing the total weighted ear-liness and tardiness of a set of jobs. We propose a time-indexed mathematical formulation for representing the problem, new valid constraints families for this formulatio...

This article presents a multi-agent framework for optimization using metaheuristics, called AMAM. In this proposal, each agent acts independently in the search space of a combinatorial optimization problem. Agents share information and collaborate with each other through the environment. The goal is to enable the agent to modify their actions based...

This paper addresses the multiobjective hybrid flow shop (MOHFS) scheduling problem. In the MOHFS problem considered here, we have a set of jobs that must be performed in a set of stages. At each stage, we have a set of unrelated parallel machines. Some jobs may skip stages. The evaluation criteria are the minimizations of makespan, the weighted su...

This paper presents an implementation of the Variable Neighborhood Search (VNS) metaheuristic for solving the optimization version of the Multidimensional Multi-Way Number Partitioning Problem (MDMWNPP). This problem consists in distributing the vectors of a given sequence into k disjoint subsets such that the sums of each subset form a set of vect...

This paper addresses the double vehicle routing problem with multiple stacks (DVRPMS) in which a fleet of vehicles must collect items in a pickup region and then travel to a delivery region where all items are delivered. The load compartment of all vehicles is divided into rows (horizontal stacks) of fixed profundity (horizontal heights), and on ea...

This paper extends some explanations about the convergence of a type of Evolution Strategies guided by Neighborhood Structures, the Neighborhood Guided Evolution Strategies. Different well-known Neighborhood Structures commonly applied to Vehicle Routing Problems are used to highlight the evolution of the move operators during the evolutionary proc...

The School Timetabling Problem is widely known and it appears at the beginning of the school term of the institutions. Due to its complexity, it is usually solved by heuristic methods. In this work, we developed two algorithms based on the Variable Neighborhood Search (VNS) metaheuristic. The first one, named Skewed General Variable Neighborhood Se...

The Multi-Depot Vehicle Routing Problem (MDVRP) is a variant of the Vehicle Routing Problem (VRP) that consists in designing a set of vehicle routes to serve all customers, such that the maximum number of vehicle per depot, the vehicle capacity and the maximum time for each route are respected. The objective is to minimize the total cost of transpo...

We propose a heuristic algorithm based on the Late Acceptance Hill-Climbing metaheuristic for solving the Double Vehicle Routing Problem with Multiple Stacks and Heterogeneous Demand (DVRPMSHD). In this problem, customers must be served by a fleet of vehicles, which have their containers divided into horizontal stacks, where each load/unload operat...

This work addresses the Unrelated Parallel Machine Scheduling Problem in which machine and job sequence-dependent setup time are considered. The objective is to minimize the makespan. For solving it, a Smart General Variable Neighborhood Search algorithm is proposed. It explores the solution space through five strategies: swap of jobs in the same m...

This work aims to develop a system for industrial robotic cells integration, focusing on Industry 4.0, using softPLC and 3D perception approaches. Most industrial robots use proprietary software and closed architecture drivers, and as a result, the integration with devices from different manufacturers becomes inflexible. Thus, we propose the develo...

Este trabalho trata do problema de programação de horários em escolas. Dada sua natureza combinatória, ele é resolvido por meio de dois algoritmos metaeurísticos, um baseado em Simulated Annealing e outro em GRASP Ambos possuem parâmetros auto-adaptativos, dispensando, assim, a calibragem destes. Para testá-los são utilizados dados reais do departa...

This article presents a review and a comparative analysis between frameworks for solving optimization problems using metaheuristics. The aim is to identify both the desirable characteristics as the existing gaps in the current state of the art, with a special focus on the use of multi-agent structures in the development of hybrid metaheuristics. A...

Given the important role of machine scheduling in manufacturing industry, we discuss power consumption in sequencing jobs in a scheduling problem, assuming variable speed operation in machines. The problem involves defining the allocation of jobs to machines, the order of processing jobs and the speed of processing each job in each machine. This pr...

This volume presents selected, peer-reviewed, short papers that were accepted for presentation in the 5th International Conference on Variable Neighborhood Search (ICVNS'17) which was held in Ouro Preto, Brazil, during October 2-4, 2017.

This paper focus on the learning of music time series. In this context, from compressed digital audio files, we sought to verify how a song can be learned, both in terms of amplitude and frequency. Given the enormous amount of data contained in those time series, the use of classical learning methods becomes limited. Typical compressed acquisitions...

This paper presents an algorithm based on the General Variable Neighborhood Search (GVNS) metaheuristic for solving the Multi-Depot Vehicle Routing Problem (MDVRP). The MDVRP consists in designing a set of vehicle routes serving all customers, such that the maximum number of vehicle per depot and vehicle-capacity are respected, and the total cost o...

This work addresses the multi-level capacitated minimum spanning tree (MLCMST) problem. It consists of finding a minimal cost spanning tree such that the flow to be transferred from a central node (root) to the other nodes is bounded by the edge capacities. In this paper, a hybrid algorithm, combining the Variable Neighborhood Search (VNS) metaheur...

This work implements and compares four algorithms based on Variable Neighborhood Search (VNS), named RVNS, GVNSf, GVNSr and GVNSrf, for solving the Single Machine Scheduling Problem with Earliness and Tardiness Penalties (SM-SPETP). Computational experiments showed that the algorithm GVNSf obtained better-quality solutions compared with the other a...

This work presents a hybrid multi-start algorithm for solving generic binary linear programs. This algorithm, called HMS, is based on a Multi-Start Metaheuristic and combines exact and heuristic strategies to address the problem. The initial solutions are generated by a strategy that applies linear programming and constraint propagation for definin...

This paper addresses the Hybrid Flow Shop Problem (HFSP) through the Multi-objective Variable Neighborhood Search metaheuristic (MOVNS). In this problem, we have a set of jobs that must be performed on a set of stages. At each stage, we have a set of unrelated parallel machines. Some jobs may skip stages. In this paper we considere two evaluation c...

In this work, we present an effective memetic algorithm for a transportation network reconstruction problem. The problem addressed arises when the connections of a transportation network have been destroyed by a disaster, and then need to be rebuilt by a construction crew in order to minimize the damage caused in the post-disaster phase. Each verte...

This paper addresses a problem arising in the long-term maintenance programming of an iron ore processing plant of a company in Brazil. The problem is a complex maintenance programming where we have to assign the equipment preventive programming orders to the available work teams over a 52 week planning. We first developed a general mixed integer p...

We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, "pickups and deli...