Elaboration and analysis of social indicators as an instrument to support decision making in the process of depollution of the Guanabara Bay

Despite the efforts in the depollution since the 1990s, evolution of the damaged social scenario in the region of the watershed of the Guanabara Bay is not perceived by the public opinion. The importance of social indicators emerges in a moment in which rendering account to the population regarding investiments and results obtained, orienting actions for emergency social and local issues and monitoring results for identification of adjustments to the actions for the achievement of better results is necessary. The current agenda for debating social issues of the region of the bay represented the basis for the creation of a system of social indicators. Three watersheds in depollution process were also studied, focusing on their approaches regarding social issues. A theoretical model of indicators was developed and tested in a draft of the Guanabara Bay watershed, using the public data available. The model proved to be a useful tool for an holistic approach of the bay by providing information on the better orientation of depollution actions for more effective results in both social and environmental issues.Apesar dos esforços de despoluição desde os anos 1990, não houve percepção, por parte da opinião pública, de que houve evolução do deteriorado quadro social da região da bacia da Baía de Guanabara (RJ). A importância dos indicadores sociais emerge em um momento em que se faz necessário prestar contas à população quanto aos investimentos e resultados obtidos, direcionar as ações às questões sociais e locais em situação de maior urgência e acompanhar os resultados para a identificação de ajustes nas ações para o alcance de melhores resultados. A atual agenda de discussão das questões sociais do entorno da baía configurou a base para a elaboração de um sistema de indicadores sociais. Três bacias hidrográficas em processo de despoluição também foram estudadas, com foco em suas abordagens quanto às questões sociais. Um modelo teórico de indicadores foi elaborado e testado em um recorte da bacia da Baía de Guanabara, por intermédio da utilização de dados públicos disponíveis. O modelo se mostrou ferramenta útil para uma abordagem holística da bacia ao informar sobre o melhor direcionamento de ações de despoluição para resultados mais efetivos em ambas as questões, sociais e ambientais

Dimensionality reduction for multi-criteria problems: an application to the decommissioning of oil and gas installations

This paper is motivated by decommissioning studies in the field of oil and gas, which comprise a very large number of installations and are of interest to a large number of stakeholders. Generally, the problem gives rise to complicated multi-criteria decision aid tools that rely upon the costly evaluation of multiple criteria for every piece of equipment. We propose the use of machine learning techniques to reduce the number of criteria by feature selection, thereby reducing the number of required evaluations and producing a simplified decision aid tool with no sacrifice in performance. In addition, we also propose the use of machine learning to explore the patterns of the multi-criteria decision aid tool in a training set. Hence, we predict the outcome of the analysis for the remaining pieces of equipment, effectively replacing the multi-criteria analysis by the computational intelligence acquired from running it in the training set. Computational experiments illustrate the effectiveness of the proposed approach

Optimisation and control of the supply of blood bags in hemotherapic centres via Markov Decision Process with discounted arrival rate

Running a cost-effective human blood transfusion supply chain challenges decision makers in blood services world-wide. In this paper, we develop a Markov decision process with the objective of minimising the overall costs of internal and external collections, storing, producing and disposing of blood bags, whilst explicitly considering the probability that a donated blog bag will perish before demanded. The model finds an optimal policy to collect additional bags based on the number of bags in stock rather than using information about the age of the oldest item. Using data from the literature, we validate our model and carry out a case study based on data from a large blood supplier in South America. The study helped achieve an overall increase of 4.5% in blood donations in one year

Modeling the integrated mine-to-client supply chain: a survey

Mining is an important economic activity and a highly complex industry. As such, it demands a complex supply chain to connect mines to clients, often involving railways, ports and long-distance maritime shipping. State-of-the-art optimization tools are an invaluable asset to help manage such a complex environment, which makes mining industry a very fertile ground for operational research applications. This paper aims to present a bibliographical review of published works involving operational research applications in the mining industry. We start by mapping applications within each isolated link of the chain. Then, we make inroads into the researches involving and connecting multiple links of the mining chain. Finally, we present summaries of our finding and pinpoint some directions for research opportunities in the mining industry

Using multiflow formulations to solve the Steiner tree problem in graphs

We present three different mixed integer linear models with a polynomial number of variables and constraints for the Steiner tree problem in graphs. The linear relaxations of these models are compared to show that a good (strong) linear relaxation can be a good approximation for the problem. We present computational results for the STP OR-Library (J.E. Beasley) instances of type b, c, d and e

Optimization model to assess electric vehicles as an alternative for fleet composition in station-based car sharing systems

Electromobility can be one of many solutions to the environmental challenge facing society nowadays, and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimization model to evaluate the influence of the selected parameters in the economic and environmental dimensions of different vehicle technologies and the optimal fleet composition for small-scale car sharing. The model is applied to car sharing system VAMO, located in Fortaleza (Brazil), and the decision variables comprise pure electric (BEV), plug-in hybrid (PHEV) and internal combustion engine (ICEV) vehicles. Baseline results are strongly influenced by the economic dimension, showing that existing infrastructure and well-established technology are great advantages for ICEVs and major barriers for EVs. In that sense, ethanol arises as a balanced alternative between costs and emissions. However, EVs represent a strong environmental appeal considering global emissions and local pollutants and even with economic losses in the short-term, investments in electromobility could come out as a positioning strategy in a future business with strong perspectives of growth, be it technological or in market share. The results suggest that all vehicle technologies will play an important role during this transition period to a desired sustainable mobility.</p

Integrating berth allocation decisions in a fleet composition and periodic routing problem of platform supply vessels

The aim of this work is to present mathematical models and a heuristic solution strategy to solve the heterogeneous fleet-sizing problem of platform supply vessels (PSVs) that support the offshore oil and gas exploration and production (E&amp;P) activities. The problem considered in this research takes into account a novel characteristic related to the berth allocation problem of the supply base, which must be considered together with the decisions of selecting the departure days and the routes. The adopted solution strategy consists of sequentially solving models that capture different aspects of the problem, by starting with models that are simpler to solve. The solution found in one step provides a lower bound to the next step. This procedure was devised in order to reduce the search space and to speed up convergence. The proposed solution strategy was applied to real instances in Brazil, which has up to 79 offshore units grouped into clusters, with fair/acceptable results. The procedure allowed for assessing the impact of the number of berths on the fleet composition

A branch-andcut algorithm for equitable coloring based on a formulation by representatives, Electr

Abstract An equitable k-coloring of a graph is defined by a partition of its vertices into k disjoint stable subsets, such that the difference between the cardinalities of any two subsets is at most one. The equitable coloring problem consists of finding the minimum value of k such that a given graph can be equitably k-colored. We present two new integer programming formulations based on representatives for the equitable coloring problem. We propose a primal constructive heuristic, branching strategies, and the first branch-and-cut algorithm in the literature of the equitable coloring problem. The computational experiments were carried out on randomly generated graphs, DIMACS graphs, and other graphs from the literature