cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19967736.v1
title: PORTFOLIO IMPACT INVESTMENT MANAGEMENT USING MULTI-OBJECTIVE OPTIMIZATION

description: ABSTRACT The main goal of this paper is to propose a methodology for selecting investment portfolios designed to generate financial returns and a socio-environmental impact. This work suggests a seven-step protocol that prioritizes the use of scientific evidence, quality data sources and the interdependence of investment alternatives. In particular, it proposes a multi-objective evolutionary optimization model to estimate the efficient frontier and select the portfolio according to the decision maker’s preferences. By an innovative extension of the concept of portfolio diversification, already well understood in traditional portfolio management, this study concludes that it is possible for impact investors to build more efficient portfolios. Due to the scarcity of similar studies in the literature and the rare use of rigorous methods for implementing impact investments, this study, therefore, presents an academic contribution to the field and illustrates the use of the proposed methodology to improve management decisions.
DOI: 10.6084/m9.figshare.19967739
title: INTEGRATED PRODUCTION-DISTRIBUTION SYSTEMS: TRENDS AND PERSPECTIVES

description: ABSTRACT During the last two decades, integrated production-distribution problems have attracted a great deal of attention in the operations research literature. Within a short period, a large number of papers have been published and the field has expanded dramatically. The purpose of this paper is to provide a comprehensive review of the existing literature by classifying the existing models into several different categories based on multiple characteristics. The paper also discusses some trends and list promising avenues for future research.
DOI: 10.6084/m9.figshare.19967739.v1
title: INTEGRATED PRODUCTION-DISTRIBUTION SYSTEMS: TRENDS AND PERSPECTIVES

description: ABSTRACT During the last two decades, integrated production-distribution problems have attracted a great deal of attention in the operations research literature. Within a short period, a large number of papers have been published and the field has expanded dramatically. The purpose of this paper is to provide a comprehensive review of the existing literature by classifying the existing models into several different categories based on multiple characteristics. The paper also discusses some trends and list promising avenues for future research.
DOI: 10.6084/m9.figshare.19967737
title: MATHEMATICAL MODELING OF TOW TRUCKS LOCATION CONSIDERING TRAFFIC CONGESTION QUEUE

description: ABSTRACT We propose a mathematical model including queueing theory to reduce the negative consequences generated by large queues of vehicles as a result of traffic incidents. The mathematical model maximizes the number of incidents’ responses, and minimizes the non-recurrent congestion generated by them, considering a predetermined time to clear them, and an average or maximum response time. The model is applied to real-world incident data from Avenida Brasil, Rio de Janeiro, and the results showed that it is possible to concentrate the attendance in the critical areas of the expressway. The mathematical model proposed in this work can be used as a decision tool to help the government defining the acceptable average time for incident response, and the number of tow trucks necessary to achieve a pre-established service level.
DOI: 10.6084/m9.figshare.19967737.v1
title: MATHEMATICAL MODELING OF TOW TRUCKS LOCATION CONSIDERING TRAFFIC CONGESTION QUEUE

description: ABSTRACT We propose a mathematical model including queueing theory to reduce the negative consequences generated by large queues of vehicles as a result of traffic incidents. The mathematical model maximizes the number of incidents’ responses, and minimizes the non-recurrent congestion generated by them, considering a predetermined time to clear them, and an average or maximum response time. The model is applied to real-world incident data from Avenida Brasil, Rio de Janeiro, and the results showed that it is possible to concentrate the attendance in the critical areas of the expressway. The mathematical model proposed in this work can be used as a decision tool to help the government defining the acceptable average time for incident response, and the number of tow trucks necessary to achieve a pre-established service level.
DOI: 10.6073/pasta/24a1bc525218420ee3c138caf7246e00
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 2 meteorological station: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data at 10 cm at CSIS Block-2. Collection of soil volumetric water content data at Jornada LTER Cross-scale Interactions Study (CSIS) blocks, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Soil volumetric water content is measured at 10 cm depth at 3 locations at each of the 4 plots per block. The locations in each plot are under bare soil, under perennial grass, and under shrub. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are recorded every 30 minutes at an automated meteorological station installed at Jornada LTER CSIS Block-2 site. This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.19967746
title: LOT SIZING AND CUTTING STOCK PROBLEMS IN A PAPER PRODUCTION PROCESS

description: ABSTRACT In many manufacturing industries, the production process involves the production of objects and the cutting of such objects into smaller pieces in order to meet a specific demand. In the optimization of these processes, one can identify the lot sizing and the cutting stock problems. In the literature, these problems are mostly separately dealt. However, treating these two problems in an integrated approach can decrease overall costs. In this research, we deal with the coupled lot sizing and cutting stock problem. It is proposed a mathematical formulation for the production and cutting of paper based on a real case, which considers setup costs and limited machine capacity in the production process of the objects. For the solution of the proposed model, we used a column generation approach and a relax-and-fix heuristic. Computational tests were carried out in order to analyze the methodology used in the resolution of the model. The results showed to be competitive in a reasonable computational time.
DOI: 10.6084/m9.figshare.19967746.v1
title: LOT SIZING AND CUTTING STOCK PROBLEMS IN A PAPER PRODUCTION PROCESS

description: ABSTRACT In many manufacturing industries, the production process involves the production of objects and the cutting of such objects into smaller pieces in order to meet a specific demand. In the optimization of these processes, one can identify the lot sizing and the cutting stock problems. In the literature, these problems are mostly separately dealt. However, treating these two problems in an integrated approach can decrease overall costs. In this research, we deal with the coupled lot sizing and cutting stock problem. It is proposed a mathematical formulation for the production and cutting of paper based on a real case, which considers setup costs and limited machine capacity in the production process of the objects. For the solution of the proposed model, we used a column generation approach and a relax-and-fix heuristic. Computational tests were carried out in order to analyze the methodology used in the resolution of the model. The results showed to be competitive in a reasonable computational time.
DOI: 10.6084/m9.figshare.19967748
title: A DECOMPOSITION APPROACH FOR THE TWO-STAGE STOCHASTIC SUPPLY NETWORK PLANNING IN LIGHT OF THE ROLLING HORIZON PRACTICE

description: ABSTRACT Industries conduct the Sales and Operations Planning (S&OP) to balance demand and supply aligned to business targets. This study aims at proposing a model and an algorithm for the tactical supply chain planning admitting uncertainty and reflecting the peculiar S&OP aspect of rolling horizon planning. Therefore, a two-stage stochastic programming model is developed and solved via a multi-cut Benders decomposition algorithm. The model and the solution method are evaluated by numerical experiments and a case study. Results show that the optimal supply chain profit is not proportional to demand, in fact, an increase in demand can even decrease the optimal profit due to capacity constraints along the supply chain. Such findings reinforce that profitability and service level are increased with the synergy of the sales team with production, distribution and procurement team on establishing which demand should be satisfied - or not - in each period. The stochastic solution is compared to deterministic approaches.
DOI: 10.6084/m9.figshare.19967748.v1
title: A DECOMPOSITION APPROACH FOR THE TWO-STAGE STOCHASTIC SUPPLY NETWORK PLANNING IN LIGHT OF THE ROLLING HORIZON PRACTICE

description: ABSTRACT Industries conduct the Sales and Operations Planning (S&OP) to balance demand and supply aligned to business targets. This study aims at proposing a model and an algorithm for the tactical supply chain planning admitting uncertainty and reflecting the peculiar S&OP aspect of rolling horizon planning. Therefore, a two-stage stochastic programming model is developed and solved via a multi-cut Benders decomposition algorithm. The model and the solution method are evaluated by numerical experiments and a case study. Results show that the optimal supply chain profit is not proportional to demand, in fact, an increase in demand can even decrease the optimal profit due to capacity constraints along the supply chain. Such findings reinforce that profitability and service level are increased with the synergy of the sales team with production, distribution and procurement team on establishing which demand should be satisfied - or not - in each period. The stochastic solution is compared to deterministic approaches.
DOI: 10.6084/m9.figshare.19967754
title: DECOMPOSITION BASED HEURISTICS FOR A LOT SIZING AND SCHEDULING PROBLEM ON MULTIPLE HETEROGENEOUS PRODUCTION LINES WITH PERISHABLE PRODUCTS

description: ABSTRACT In this paper, we propose a novel MIP-based heuristic method to deal with a lot sizing and scheduling problem with multiple heterogeneous production lines in a production setting with perishable items. The problem is inspired by the production processes adopted by some Brazilian food industries and it considers that several production lines share the same scarce production resources. Therefore, only a subset of those lines can simultaneously operate in each production period. Moreover, the production environment is characterized by the existence of sequence-dependent setup times and costs, and by the production of perishable items which can be stocked for a short period only. Firstly, we propose a facility location reformulation for a model previously proposed in the literature. Secondly, we propose a heuristic composed of two phases. The first phase has an elaborated approach to building feasible solutions solving initially an aggregated lot sizing problem to decide which production lines to assemble, followed by the resolution of the various single line lot sizing and scheduling problems. The second phase applies improvement heuristics exploring principles of fix-and-optimize and local branching procedures. Computational results carried out using a data set proposed in the literature are presented in order to study the efficiency of the proposed approach. The results demonstrate that our heuristics provide superior results when benchmarked with a heuristic from the literature specifically developed to solve the problem under consideration, and with a commercial MIP solver.
DOI: 10.6084/m9.figshare.19967754.v1
title: DECOMPOSITION BASED HEURISTICS FOR A LOT SIZING AND SCHEDULING PROBLEM ON MULTIPLE HETEROGENEOUS PRODUCTION LINES WITH PERISHABLE PRODUCTS

description: ABSTRACT In this paper, we propose a novel MIP-based heuristic method to deal with a lot sizing and scheduling problem with multiple heterogeneous production lines in a production setting with perishable items. The problem is inspired by the production processes adopted by some Brazilian food industries and it considers that several production lines share the same scarce production resources. Therefore, only a subset of those lines can simultaneously operate in each production period. Moreover, the production environment is characterized by the existence of sequence-dependent setup times and costs, and by the production of perishable items which can be stocked for a short period only. Firstly, we propose a facility location reformulation for a model previously proposed in the literature. Secondly, we propose a heuristic composed of two phases. The first phase has an elaborated approach to building feasible solutions solving initially an aggregated lot sizing problem to decide which production lines to assemble, followed by the resolution of the various single line lot sizing and scheduling problems. The second phase applies improvement heuristics exploring principles of fix-and-optimize and local branching procedures. Computational results carried out using a data set proposed in the literature are presented in order to study the efficiency of the proposed approach. The results demonstrate that our heuristics provide superior results when benchmarked with a heuristic from the literature specifically developed to solve the problem under consideration, and with a commercial MIP solver.
DOI: 10.6084/m9.figshare.19967755
title: INTEGRATED LOTSIZING, SCHEDULING AND BLENDING DECISIONS IN THE SPINNING INDUSTRY

description: ABSTRACT In this paper, the relevance of integrated planning concerning decisions of production and blending in a spinning industry is studied. The scenario regards a plant that produces several yarn packages over a planning horizon. Each yarn type is produced using a blend of several cotton bales that must contain attributes to ensure the quality of the produced yarns. Three approaches to managing production and blending are compared; the first deals with the solution to the production scheduling and blending problems in a single integrated model. The second approach hierarchically addresses these problems. The third procedure combines features from the integrated and hierarchical approaches. These approaches are applied to a real-world problem, and their respective performances are analyzed. The third approach proved to deal with lot sizing, scheduling and blending in the spinning industry more efficiently. Moreover, the results indicate the importance of coordinating production and blending decisions.
DOI: 10.6084/m9.figshare.19967755.v1
title: INTEGRATED LOTSIZING, SCHEDULING AND BLENDING DECISIONS IN THE SPINNING INDUSTRY

description: ABSTRACT In this paper, the relevance of integrated planning concerning decisions of production and blending in a spinning industry is studied. The scenario regards a plant that produces several yarn packages over a planning horizon. Each yarn type is produced using a blend of several cotton bales that must contain attributes to ensure the quality of the produced yarns. Three approaches to managing production and blending are compared; the first deals with the solution to the production scheduling and blending problems in a single integrated model. The second approach hierarchically addresses these problems. The third procedure combines features from the integrated and hierarchical approaches. These approaches are applied to a real-world problem, and their respective performances are analyzed. The third approach proved to deal with lot sizing, scheduling and blending in the spinning industry more efficiently. Moreover, the results indicate the importance of coordinating production and blending decisions.
DOI: 10.6084/m9.figshare.19967758
title: ALTERNATIVES FOR THE COMPOSITION OF INTERACTIVE ENVIRONMENTAL IMPACT FACTORS

description: ABSTRACT Composition of probabilistic preferences is applied here together with life cycle assessment in the evaluation of sewage sludge treatment scenarios. The computations are based on the transformation of preferences for the alternatives elicited applying each criterion into probabilities of being the best. Different forms of probabilistic composition are applied and the possibility of interaction between factors is considered. The results are compared to results previously obtained with different forms of composition modeling the interaction or assuming linearity. Eight scenarios combining different processing techniques and leading to distinct end-uses are compared. These scenarios are ranked combining probabilities of preference according to five environmental impact factors: water use, energy consumption, carbon footprint, human toxicity potential and terrestrial ecotoxicity potential. In the large spectrum of views that the probabilistic approach provides, evidence is found favoring a system that includes recovery of energy to be used in a dryer and in a cement kiln.
DOI: 10.6084/m9.figshare.19967758.v1
title: ALTERNATIVES FOR THE COMPOSITION OF INTERACTIVE ENVIRONMENTAL IMPACT FACTORS

description: ABSTRACT Composition of probabilistic preferences is applied here together with life cycle assessment in the evaluation of sewage sludge treatment scenarios. The computations are based on the transformation of preferences for the alternatives elicited applying each criterion into probabilities of being the best. Different forms of probabilistic composition are applied and the possibility of interaction between factors is considered. The results are compared to results previously obtained with different forms of composition modeling the interaction or assuming linearity. Eight scenarios combining different processing techniques and leading to distinct end-uses are compared. These scenarios are ranked combining probabilities of preference according to five environmental impact factors: water use, energy consumption, carbon footprint, human toxicity potential and terrestrial ecotoxicity potential. In the large spectrum of views that the probabilistic approach provides, evidence is found favoring a system that includes recovery of energy to be used in a dryer and in a cement kiln.
DOI: 10.6084/m9.figshare.19967761
title: ROBUST SOLUTION IDENTIFICATION FOR UNCERTAINTY MANAGEMENT IN MOLP - AN INTERACTIVE APPROACH

description: ABSTRACT This paper presents a robust deterministic method for the treatment of uncertainty in decision-making systems based on Sonar Method. It introduces uncertainty into mathematical models as interval numbers. This work proposes an interactive approach that identifies the efficient vertices of the Multiobjective Linear Programming (MOLP), where some or all the coefficients of the objective functions, constraints or limits of the constraints are interval of real numbers. The method identifies robust solutions to MOLP under uncertainty, showing how the interactive approach presented in this paper can provide the possibility of exploring in new decision support methodologies.
DOI: 10.6084/m9.figshare.19967761.v1
title: ROBUST SOLUTION IDENTIFICATION FOR UNCERTAINTY MANAGEMENT IN MOLP - AN INTERACTIVE APPROACH

description: ABSTRACT This paper presents a robust deterministic method for the treatment of uncertainty in decision-making systems based on Sonar Method. It introduces uncertainty into mathematical models as interval numbers. This work proposes an interactive approach that identifies the efficient vertices of the Multiobjective Linear Programming (MOLP), where some or all the coefficients of the objective functions, constraints or limits of the constraints are interval of real numbers. The method identifies robust solutions to MOLP under uncertainty, showing how the interactive approach presented in this paper can provide the possibility of exploring in new decision support methodologies.
DOI: 10.6084/m9.figshare.19967764
title: MULTIPLE CHOICE METHOD WITH GENETIC ALGORITHM FOR THE FORMATION OF SOCCER TEAMS

description: ABSTRACT For soccer managers, player selection lineups are a key process for better performance, both on financial and sports matters. However, to determine a quality solution to this problem it becomes more complex, as the number of alternatives and criteria increases and the number of viable solutions grows ex ponentially. This paper proposes a multicriteria method with genetic algorithm for the evaluation of soccer teams based on Brazilian Championship data. A team complementation percentage was calculated con sidering a total of 322 athletes and 18 criteria. The results presented a 3-6-1 format as the ideal for this case study, obtaining a team complementation value of 43.04%. The method adaptability for the decision-maker is highlighted, showing it was possible to determinate the most complementary team according to the desired tactical formation and importance attributed for each criterion.
DOI: 10.6084/m9.figshare.19967764.v1
title: MULTIPLE CHOICE METHOD WITH GENETIC ALGORITHM FOR THE FORMATION OF SOCCER TEAMS

description: ABSTRACT For soccer managers, player selection lineups are a key process for better performance, both on financial and sports matters. However, to determine a quality solution to this problem it becomes more complex, as the number of alternatives and criteria increases and the number of viable solutions grows ex ponentially. This paper proposes a multicriteria method with genetic algorithm for the evaluation of soccer teams based on Brazilian Championship data. A team complementation percentage was calculated con sidering a total of 322 athletes and 18 criteria. The results presented a 3-6-1 format as the ideal for this case study, obtaining a team complementation value of 43.04%. The method adaptability for the decision-maker is highlighted, showing it was possible to determinate the most complementary team according to the desired tactical formation and importance attributed for each criterion.
DOI: 10.6084/m9.figshare.19967767
title: ENDOGENEITY IN STOCHASTIC PRODUCTION FRONTIER WITH ONE AND TWO-STEP MODELS: AN APPLICATION WITH MUNICIPAL DATA FROM THE BRAZILIAN AGRICULTURAL CENSUS

description: ABSTRACT Stochastic production frontier models are widely used in microeconometrics and, in the last decades, have been proven to be versatile in their range of applications. However, there are few studies concerning endogeneity in stochastic production frontier models. Here we present two stochastic production frontier models with endogenous variables based on the main distributions for the technical inefficiency. We also derive analytic gradient vectors to obtain the best performance at a reasonable computational time cost. The methodology presented here is based on one and two-step maximum likelihood estimation, allows for endogeneity and heteroscedasticity in relation to one or both error terms, and is implemented in R language. Finally, we illustrate an application with municipal data from the Brazilian agricultural census. The results show that capital dominates the production function, credit access and technical assistance are endogenous, and income concentration seems to impede productive inclusion through the more intensive use of technology.