RESUMO

Traditional methods for designing concrete mixtures provide good results; however, they do not guarantee the optimum composition. Consequently, applying operational research techniques is motivated by an increasing need for designers to proportion the concrete's raw materials that satisfy the concrete performance requirements such as mechanical properties, chemical properties, workability, sustainability, and cost. For this reason, many authors have been looking for mathematical programming and machine learning solutions to predict concrete mix properties and optimise concrete mixtures. Therefore, a comprehensive review of operational research techniques concerning the design and proportioning of concrete mixtures and a classification framework are presented herein.

RESUMO

Healthcare service centers must be sited in strategic locations that meet the immediate needs of patients. The current situation due to the COVID-19 pandemic makes this problem particularly relevant. Assume that each center corresponds to an assigned place for vaccination and that each center uses one or more vaccine brands/laboratories. Then, each patient could choose a center instead of another, because she/he may prefer the vaccine from a more reliable laboratory. This defines an order of preference that might depend on each patient who may not want to be vaccinated in a center where there are only her/his non-preferred vaccine brands. In countries where the vaccination process is considered successful, the order assigned by each patient to the vaccination centers is defined by incentives that local governments give to their population. These same incentives for foreign citizens are seen as a strategic decision to generate income from tourism. The simple plant/center location problem (SPLP) is a combinatorial approach that has been extensively studied. However, a less-known natural extension of it with order (SPLPO) has not been explored in the same depth. In this case, the size of the instances that can be solved is limited. The SPLPO considers an order of preference that patients have over a set of facilities to meet their demands. This order adds a new set of constraints in its formulation that increases the complexity of the problem to obtain an optimal solution. In this paper, we propose a new two-stage stochastic formulation for the SPLPO (2S-SPLPO) that mimics the mentioned pandemic situation, where the order of preference is treated as a random vector. We carry out computational experiments on simulated 2S-SPLPO instances to evaluate the performance of the new proposal. We apply an algorithm based on Lagrangian relaxation that has been shown to be efficient for large instances of the SPLPO. A potential application of this new algorithm to COVID-19 vaccination is discussed and explored based on sensor-related data. Two further algorithms are proposed to store the patient's records in a data warehouse and generate 2S-SPLPO instances using sensors.

Assuntos

RESUMO

A solution strategy based on integer linear programming models has been developed for leaf sweeping operations in the Argentine city of Trenque Lauquen. The aim is to achieve efficiency in the assignment of sweepers to city blocks, the identification of leaf bag deposit points and the routes to be followed by collection trucks for leaf bag pickup. Previous to this strategy, sweeper assignments were improvised and inefficient, with blocks often left unswept. Furthermore, no method was available for accurately determining the number of sweepers needed to ensure either full coverage of all city zones within the working day or a balanced work load distribution across all sweepers. Application of the solution strategy by the city has resulted in efficient definitions of sweeper requirements while optimizing sweeper assignments such that all blocks are covered. Once the strategy is fully implemented, the number of bag deposit points under the manual definitions should be reduced by roughly one-half and the total travel distance of the truck routes, modelled as an asymmetric travelling salesman problem, should be cut by 10-15% with the consequent savings in time, vehicle use and fuel consumption.

Assuntos

RESUMO

The application of optimization methods to forest management has given rise to a successful line of investigation in recent decades. However, there have been few publications associated with the application of these techniques to the management of industrial forest plantations (those with short or medium rotations, always less than 50 years), which consider the important role played by these forest systems in the supply of diverse goods and services. This study presents an overview of this literature which, by analyzing 67 articles published in journals contained in the ISI Web of Science, highlight, among other aspects, the techniques employed, their evolution, their planning type (strategic, tactical or operational), the functional objectives and constraints considered, or the type of software deployed in these studies. The results show how Model I has been the one most frequently used in these studies, and how the spatial component is increasing in importance. However, classic optimization methods, such as mixed integer programming, have been those most commonly resorted to, although the employment of multi-criteria techniques such as goal programming and analytic hierarchical process have strongly emerged in recent years.

Assuntos

RESUMO

The application of optimization methods to forest management has given rise to a successful line of investigation in recent decades. However, there have been few publications associated with the application of these techniques to the management of industrial forest plantations (those with short or medium rotations, always less than 50 years), which consider the important role played by these forest systems in the supply of diverse goods and services. This study presents an overview of this literature which, by analyzing 67 articles published in journals contained in the ISI Web of Science, highlight, among other aspects, the techniques employed, their evolution, their planning type (strategic, tactical or operational), the functional objectives and constraints considered, or the type of software deployed in these studies. The results show how Model I has been the one most frequently used in these studies, and how the spatial component is increasing in importance. However, classic optimization methods, such as mixed integer programming, have been those most commonly resorted to, although the employment of multi-criteria techniques such as goal programming and analytic hierarchical process have strongly emerged in recent years.(AU)

Assuntos

RESUMO

Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment.

RESUMO

In this paper we propose a mathematical programming model to optimize the tactical planning of the surgery service of a complex Colombian Hospital by using efficiently its resources, seeking for greater financial incomes and analyzing its capacity. In the model, we consider the main resources involved before, during and after surgical procedures. The main results are: a) the post-operatory beds, especially in the intensive care unit (ICU) and at the surgical ward, are the limiting resource of the capacity of this service; b) There is an average underutilization of 48.4% in operating rooms and 33% in the available human resources (mainly surgeons and anesthesiologist); d) reducing the duration of the pre- and post-surgery stay is an option to increase the availability of beds. Key findings suggest the following improvement options: a) Closing or disabling some operating rooms, could reduce the costs and improve the utilization of the service without jeopardizing the fulfilment of its demand; b) working on the increase of the demand for outpatient surgeries could be a good option, since they do not require additional beds; c) combining the closure of operating rooms and the increase of demand for outpatient surgery is an interesting option.

En este trabajo se propone el modelo de programación matemática para optimizar la planificación táctica del servicio de cirugía de un complejo hospitalario de Colombia mediante el uso eficiente de sus recursos, en busca de mayores ingresos financieros y el análisis de su capacidad. En el modelo, se consideran los principales recursos involucrados antes, durante y después de los procedimientos quirúrgicos. Los principales resultados son los siguientes: a) las camas pos-operatorias, especialmente en la unidad de cuidados intensivos (UCI) y en la sala de cirugía, son el recurso limitante de la capacidad de este servicio; b) Existe una subutilización promedio de 48,4% en los quirófanos y el 33% en los recursos humanos disponibles (principalmente cirujanos y anestesiólogos); d) la reducción de la duración de la estancia antes y después de la cirugía es una opción para aumentar la disponibilidad de camas. Las principales conclusiones sugieren las siguientes opciones de mejora: a) Clausura o inhabilitación de algunos quirófanos, podría reducir los costos y mejorar la utilización de los servicios sin poner en peligro el cumplimiento de su demanda; b) trabajando en el aumento de la demanda de cirugías ambulatorias podría ser una buena opción, ya que no requieren camas adicionales; c) combinar el cierre de quirófanos y el aumento de la demanda de cirugía ambulatoria es una opción interesante.

Neste trabalho, é proposto o modelo de programação matemática para otimizar o planejamento tático do departamento de cirurgia de um complexo hospitalar na Colômbia através do uso eficiente dos seus recursos, em busca de rendimentos de juros e maior capacidade de análise. No modelo, são considerados os principais recursos envolvidos antes, durante e depois de procedimentos cirúrgicos. Os principais resultados são: a) as camas de pós-operatório, especialmente na unidade de terapia intensiva (UTI) e sala de cirurgia são a capacidade de recurso limitante deste serviço; b) Existe uma subutilização média de 48,4% em salas de operação e 33% em recursos humanos (principalmente cirurgiões e anestesiologistas); d) redução do tempo de permanência antes e após a cirurgia é uma opção para aumentar a disponibilidade de leitos. Os principais resultados sugerem as seguintes melhorias: a) Encerramento ou desativando algumas salas de cirurgia, poderia reduzir custos e melhorar a utilização dos serviços sem pôr em perigo o cumprimento de sua demanda; b) trabalhar para aumentar a demanda por cirurgia ambulatória pode ser uma boa opção, pois não exige camas adicionais; c) combinar o fechamento das salas de operação e a crescente demanda por cirurgia ambulatória é uma opção interessante.

RESUMO

We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.

Assuntos

RESUMO

O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.

The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.

RESUMO

The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.

O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.

RESUMO

The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.

O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.

RESUMO

The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.

O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.

RESUMO

In the farm systems modeling, the possibility of combining the pastures freely for the composition of the feeding system hinders the probabilistic evaluation of the dairy production. In this work an optimization model with a non-probabilistic approach of the uncertainty is proposed that permits to handle this problem. The application of the model for the analysis of a unit of agricultural production indicated that a decrease of the cultures of commercial grains with the constitution of pastures reserve could be an interesting strategy to minimize the economic losses if the physical revenue of the forage diminishes. Besides, because the non-statistical uncertainty modeling and the formulation of scenarios that represent technical and economic conditions that could be discussed easily with the farmer, the approach used in this work can be an useful procedure in the planning of farm systems under uncertainty.

Na modelagem de sistema de produção agropecuária, a possibilidade de combinar livremente as pastagens para a composição do sistema de alimentação dificulta a avaliação em termos probabilísticos da bovinocultura de leite. Neste trabalho, propõe-se um modelo de otimização que, utilizando uma abordagem não probabilista da incerteza, permite contornar este problema. A aplicação do modelo para a análise de uma unidade de produção agropecuária indicou que uma diminuição das culturas de grãos comerciais com a constituição de reservas de pastagens pode se constituir em uma estratégia interessante para minimizar as perdas econômicas em caso de queda de rendimento físico das forrageiras. Além disto, pelo fato de dispensar pressupostos estatísticos e basear-se em cenários que representam condições técnicas e econômicas que puderam ser facilmente discutidas com o agricultor, concluiu-se que a abordagem utilizada neste trabalho pode se constituir em um procedimento útil no planejamento de sistemas de produção sob incerteza.

RESUMO

In the farm systems modeling, the possibility of combining the pastures freely for the composition of the feeding system hinders the probabilistic evaluation of the dairy production. In this work an optimization model with a non-probabilistic approach of the uncertainty is proposed that permits to handle this problem. The application of the model for the analysis of a unit of agricultural production indicated that a decrease of the cultures of commercial grains with the constitution of pastures reserve could be an interesting strategy to minimize the economic losses if the physical revenue of the forage diminishes. Besides, because the non-statistical uncertainty modeling and the formulation of scenarios that represent technical and economic conditions that could be discussed easily with the farmer, the approach used in this work can be an useful procedure in the planning of farm systems under uncertainty.

Na modelagem de sistema de produção agropecuária, a possibilidade de combinar livremente as pastagens para a composição do sistema de alimentação dificulta a avaliação em termos probabilísticos da bovinocultura de leite. Neste trabalho, propõe-se um modelo de otimização que, utilizando uma abordagem não probabilista da incerteza, permite contornar este problema. A aplicação do modelo para a análise de uma unidade de produção agropecuária indicou que uma diminuição das culturas de grãos comerciais com a constituição de reservas de pastagens pode se constituir em uma estratégia interessante para minimizar as perdas econômicas em caso de queda de rendimento físico das forrageiras. Além disto, pelo fato de dispensar pressupostos estatísticos e basear-se em cenários que representam condições técnicas e econômicas que puderam ser facilmente discutidas com o agricultor, concluiu-se que a abordagem utilizada neste trabalho pode se constituir em um procedimento útil no planejamento de sistemas de produção sob incerteza.