cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/f72b4f31cdd760b2cff4b6bfa77b1d66
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 2 meteorological station: 5-minute summary wind and air temperature data: 2013 - ongoing

description: This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-2 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.6152309
title: RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION

description: ABSTRACT This paper presents a case study of table reservation practice for restaurant business within Walt Disney World. A unique feature here is to consider table combination to capture revenue potentials from different party sizes and at different time periods. For example, a party of large size can be served by combining two or more small tables. A mixed integer programming (MIP) model is developed to make the reservation recommendation. We propose a rolling horizon reservation policy such that the value of a particular table is periodically evaluated and updated. This is a typical revenue management method in the airlines and other industries, the essence of which is to compare the future expected revenue with a currently offered price. Using historical data, numerical test shows a significant revenue improvement potential from our proposed model.
DOI: 10.6084/m9.figshare.19967716
title: QUALITY ANALYSIS FOR THE VRP SOLUTIONS USING COMPUTER VISION TECHNIQUES

description: ABSTRACT The Vehicle Routing Problem (VRP) is a classical problem, and when the number of customers is very large, the task of finding the optimal solution can be extremely complex. It is still necessary to find an effective way to evaluate the quality of solutions when there is no known optimal solution. This work presents a suggestion to analyze the quality of vehicle routes, based only on their geometric properties. The proposed descriptors aim to be invariants in relation to the amount of customers, vehicles and the size of the covered area. Applying the methodology proposed in this work it is possible to obtain the route and, then, to evaluate the quality of solutions obtained using computer vision. Despite considering problems with different configurations for the number of customers, vehicles and service area, the results obtained with the experiments show that the proposal is useful for classifying the routes into good or bad classes. A visual analysis was performed using the Parallel Coordinates and Viz3D techniques and then a classification was performed by a Backpropagation Neural Network, which indicated an accuracy rate of 99.87%.
DOI: 10.6084/m9.figshare.6968246.v1
title: SIMULATION OPTIMIZATION IN DOSING PROCESS CONTROL SYSTEM IN REAL TIME IN A FREE AND OPEN-SOURCE SOFTWARE

description: ABSTRACT The purpose of this work is to implement an on-line control system able to adjust the production in real time applying a simulation model with algorithmic optimization and data transfer for a programmable logic controller. The Solver tool of the Excel software was integrated into a simulation software used to find the optimal dosing of input aggregates in a Hot Mix Asphalt process. Tests were carried out in different scenarios; the results demonstrated that the proposed control was effective, leading to a possible improvement in the quality of the product, enabling it to be kept within the specifications desired for most of the time. Besides, the proposed solution appeared to be simple and accessible for small companies as it applies the Excel software and a free and open-source discrete event simulation software.
DOI: 10.6084/m9.figshare.6968246
title: SIMULATION OPTIMIZATION IN DOSING PROCESS CONTROL SYSTEM IN REAL TIME IN A FREE AND OPEN-SOURCE SOFTWARE

description: ABSTRACT The purpose of this work is to implement an on-line control system able to adjust the production in real time applying a simulation model with algorithmic optimization and data transfer for a programmable logic controller. The Solver tool of the Excel software was integrated into a simulation software used to find the optimal dosing of input aggregates in a Hot Mix Asphalt process. Tests were carried out in different scenarios; the results demonstrated that the proposed control was effective, leading to a possible improvement in the quality of the product, enabling it to be kept within the specifications desired for most of the time. Besides, the proposed solution appeared to be simple and accessible for small companies as it applies the Excel software and a free and open-source discrete event simulation software.
DOI: 10.6084/m9.figshare.6967826
title: THE RANK REVERSAL PROBLEM IN MULTI-CRITERIA DECISION MAKING: A LITERATURE REVIEW

description: ABSTRACT Despite the importance of multicriteria decision-making (MCDM) techniques for constructing effective decision models, there are many criticisms due to the occurrence of a problem called rank reversal. Nevertheless, there is a lack of a systematic literature review on this important subject which involves different methods. This study reviews the pertinent literature on rank reversal, based on 130 related articles published from 1980 to 2015 in international journals, which were gathered and analyzed according to the following perspectives: multicriteria technique, year and journal in which the papers were published, co-authorship network, rank reversal types, and research goal. Thus our survey provides recommendations for future research, besides useful information and knowledge regarding rank reversal in the MCDM field.
DOI: 10.6084/m9.figshare.11313296
title: A DISCRETE DYNAMICAL SYSTEM AND ITS APPLICATIONS

description: ABSTRACT The main goal of this manuscript is to introduce a discrete dynamical system defined by symmetric matrices and a real parameter. By construction, we rediscovery the Power Iteration Method from the Projected Gradient Method. Convergence of the discrete dynamical system solution is established. Finally, we consider two applications, the first one consists in find a solution of non linear equation problem and the other one consists in verifies the optimality conditions when we solve quadratic optimization problems over linear equality constraints.
DOI: 10.6084/m9.figshare.19967721
title: A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES

description: 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 service of each vessel. Those resources, in general, are machines to load or unload vessels. The mathematical model was implemented on Cplex and can solve small scale instances, due to its high complexity. To solve larger instances, a genetic algorithm-based metaheuristic, a first-in first-out heuristic, and a machine allocation algorithm are also proposed in this paper. The model and the algorithms produce very useful and interesting results. Comparing, the results produced by the GA are, on average, 94% better than the results of the Cplex and 26% better than the results of FIFO.
DOI: 10.6084/m9.figshare.19967721.v1
title: A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES

description: 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 service of each vessel. Those resources, in general, are machines to load or unload vessels. The mathematical model was implemented on Cplex and can solve small scale instances, due to its high complexity. To solve larger instances, a genetic algorithm-based metaheuristic, a first-in first-out heuristic, and a machine allocation algorithm are also proposed in this paper. The model and the algorithms produce very useful and interesting results. Comparing, the results produced by the GA are, on average, 94% better than the results of the Cplex and 26% better than the results of FIFO.
DOI: 10.6084/m9.figshare.19967724.v1
title: AN APPLICATION OF THE IDEA MODEL IN THE ASSESSMENT OF CONTAINER TERMINALS EFFICIENCY WITH AN INTANGIBLE INPUT

description: ABSTRACT The assessment of port efficiency through Data Envelopment Analysis (DEA) is a valuable tool for ensuring accurate investment decisions in this capital-intensive industry. This study analyses the application of DEA on container ports. It assesses the efficiency of Brazilian container ports by proposing the inclusion of an intangible input related to the management practices of the terminals. In order to verify the effects of this input inclusion, the efficiency of 13 terminals is evaluated through the application of an IDEA-CRS model, which enables an appropriate handling of qualitative variables, with an orientation to the maximization of a single output, the annual container throughput, and inputs related to infrastructure, superstructure, and management unchanged. Model findings stress out the relevance of this intangible variable and the result that only three terminals are assessed as efficient, wherein the ones with the most robust management structure were not necessarily the most efficient.
DOI: 10.6084/m9.figshare.19967724
title: AN APPLICATION OF THE IDEA MODEL IN THE ASSESSMENT OF CONTAINER TERMINALS EFFICIENCY WITH AN INTANGIBLE INPUT

description: ABSTRACT The assessment of port efficiency through Data Envelopment Analysis (DEA) is a valuable tool for ensuring accurate investment decisions in this capital-intensive industry. This study analyses the application of DEA on container ports. It assesses the efficiency of Brazilian container ports by proposing the inclusion of an intangible input related to the management practices of the terminals. In order to verify the effects of this input inclusion, the efficiency of 13 terminals is evaluated through the application of an IDEA-CRS model, which enables an appropriate handling of qualitative variables, with an orientation to the maximization of a single output, the annual container throughput, and inputs related to infrastructure, superstructure, and management unchanged. Model findings stress out the relevance of this intangible variable and the result that only three terminals are assessed as efficient, wherein the ones with the most robust management structure were not necessarily the most efficient.
DOI: 10.6084/m9.figshare.19967722
title: APPLICATION OF THE ELECTRE TRI METHOD FOR SUPPLIER CLASSIFICATION IN SUPPLY CHAINS

description: ABSTRACT The present research aims to propose a Supplier Selection Model that creates collaborative relationships in Supply Chains, so that suppliers can be previously categorized into the cooperation, the coordination and the collaboration levels. Applied, quantitative, exploratory and descriptive research methods were used. A bibliographical research, a questionnaire, and the quantitative modeling were adopted as methodological procedures. The managers responsible for the Supplier Selection process in the Brazilian Wind Energy companies participated in this research. First, a criteria framework for the Selection of Supplier of goods and services was developed. Second, a Multicriteria Decision Aiding Model was created and validated, enabling the classification of the suppliers according to the relationship levels in a systematic way in terms of their performance from a set of criteria by implementing the ELECTRE TRI method. Firms can use the Model periodically in order to revise the supplier assessment and, if needed, direct them to either an inferior or superior class.
DOI: 10.6084/m9.figshare.19967722.v1
title: APPLICATION OF THE ELECTRE TRI METHOD FOR SUPPLIER CLASSIFICATION IN SUPPLY CHAINS

description: ABSTRACT The present research aims to propose a Supplier Selection Model that creates collaborative relationships in Supply Chains, so that suppliers can be previously categorized into the cooperation, the coordination and the collaboration levels. Applied, quantitative, exploratory and descriptive research methods were used. A bibliographical research, a questionnaire, and the quantitative modeling were adopted as methodological procedures. The managers responsible for the Supplier Selection process in the Brazilian Wind Energy companies participated in this research. First, a criteria framework for the Selection of Supplier of goods and services was developed. Second, a Multicriteria Decision Aiding Model was created and validated, enabling the classification of the suppliers according to the relationship levels in a systematic way in terms of their performance from a set of criteria by implementing the ELECTRE TRI method. Firms can use the Model periodically in order to revise the supplier assessment and, if needed, direct them to either an inferior or superior class.
DOI: 10.6084/m9.figshare.19967727
title: MULTI-CRITERIA DECISION SUPPORT TO CRIMINOLOGY BY GRAPH THEORY AND COMPOSITION OF PROBABILISTIC PREFERENCES

description: ABSTRACT This study associates graph theory and a multi-criteria decision aid technique, presenting a different process for doing the investigation of criminal networks. In the criminal subject, privacy concerns limit identification. For this reason, the database composed of 110 actors, involving criminals and peripheral characters to the network, was identified by numbers, without names and penalties. The discrimination of critical actors in criminal networks can help law enforcement officers to conduct a more detailed investigation for their disruption. Communication between drug traffickers was transformed into different centrality indices for each actor in their social network. Centralities and actors compose a decision matrix, analyzed by the Composition of Probabilistic Preferences to identify the most relevant actors in the criminal network. Results indicated that the five actors highlighted in the real investigation have a clear distinction of importance in the network, which in a way have been ratified.
DOI: 10.6084/m9.figshare.19967727.v1
title: MULTI-CRITERIA DECISION SUPPORT TO CRIMINOLOGY BY GRAPH THEORY AND COMPOSITION OF PROBABILISTIC PREFERENCES

description: ABSTRACT This study associates graph theory and a multi-criteria decision aid technique, presenting a different process for doing the investigation of criminal networks. In the criminal subject, privacy concerns limit identification. For this reason, the database composed of 110 actors, involving criminals and peripheral characters to the network, was identified by numbers, without names and penalties. The discrimination of critical actors in criminal networks can help law enforcement officers to conduct a more detailed investigation for their disruption. Communication between drug traffickers was transformed into different centrality indices for each actor in their social network. Centralities and actors compose a decision matrix, analyzed by the Composition of Probabilistic Preferences to identify the most relevant actors in the criminal network. Results indicated that the five actors highlighted in the real investigation have a clear distinction of importance in the network, which in a way have been ratified.
DOI: 10.6084/m9.figshare.19967728
title: HORIZON-OPTIMIZED WEIGHTS FOR FORECAST COMBINATION WITH CROSS-LEARNING

description: ABSTRACT Recent empirical results show that forecast combinations and cross-learning schemes are winning approaches in the time series field. Although many competition-winning combination methods - with cross-learning or not - use static weights along the forecasting horizon, we could not find extensive work about the effects of using horizon-optimized weights. This paper proposes a forecast combination framework and provides a considerably sizeable empirical investigation into the use of horizon-optimized weights, i.e., weights that may vary over the forecasting horizon. We build on cross-learning, time series clustering and cross-validation to form Horizon-Optimized Convex Combinations (HOC2) of forecasts from five methods: Automated exponential smoothing, Automated ARIMA, Theta, TBATS, and Seasonal naïve. Our combinations were tested with data from the previous M1, M3 and M4 forecast competitions, comprising 104,004 time series with different frequencies and lengths. The results shall be helpful to support future research on how horizon-optimized weights can be used interchangeably with static ones.
DOI: 10.6084/m9.figshare.19967728.v1
title: HORIZON-OPTIMIZED WEIGHTS FOR FORECAST COMBINATION WITH CROSS-LEARNING

description: ABSTRACT Recent empirical results show that forecast combinations and cross-learning schemes are winning approaches in the time series field. Although many competition-winning combination methods - with cross-learning or not - use static weights along the forecasting horizon, we could not find extensive work about the effects of using horizon-optimized weights. This paper proposes a forecast combination framework and provides a considerably sizeable empirical investigation into the use of horizon-optimized weights, i.e., weights that may vary over the forecasting horizon. We build on cross-learning, time series clustering and cross-validation to form Horizon-Optimized Convex Combinations (HOC2) of forecasts from five methods: Automated exponential smoothing, Automated ARIMA, Theta, TBATS, and Seasonal naïve. Our combinations were tested with data from the previous M1, M3 and M4 forecast competitions, comprising 104,004 time series with different frequencies and lengths. The results shall be helpful to support future research on how horizon-optimized weights can be used interchangeably with static ones.
DOI: 10.26300/e6ps-ts73
title: Data for "Nativity Penalty, Legal Status Paradox: The Effects of Nativity and Legal Status Signals in the U.S. Labor Market"
DOI: 10.6084/m9.figshare.19967731
title: A CHEMICAL REACTION OPTIMIZATION ALGORITHM FOR PHASOR MEASUREMENT UNIT PLACEMENT

description: ABSTRACT Optimal Phasor Measurement Unit (PMU) Placement (OPP) aims to reduce equipment costs while maintaining electrical systems observability. PMUs synchronized phasor data provide electrical systems information with high quality and frequency enabling the implementation of faster than real-time state estimators. We applied Chemical Reaction Optimization (CRO) method at OPP problem, testing it successfully at IEEE power system databases (14, 30, 57 and 118 bars) through two distinct models. The relationships between CRO parameters and the occurrence of elementary reactions was exploited, achieving better results through specific reactions. Due to problems similarity and larger scales, the software was adapted to Beasley OR-Library Set Covering (SC) problems. In the process to achieve GAPs smaller than 10% for some files, we tried out dedicated local searches, disturbance recurrence limits and stop condition changes. However, we suggest continuing to evaluate CRO method adherence to SC problem using different data structures to decrease computational times.
DOI: 10.6084/m9.figshare.19967731.v1
title: A CHEMICAL REACTION OPTIMIZATION ALGORITHM FOR PHASOR MEASUREMENT UNIT PLACEMENT

description: ABSTRACT Optimal Phasor Measurement Unit (PMU) Placement (OPP) aims to reduce equipment costs while maintaining electrical systems observability. PMUs synchronized phasor data provide electrical systems information with high quality and frequency enabling the implementation of faster than real-time state estimators. We applied Chemical Reaction Optimization (CRO) method at OPP problem, testing it successfully at IEEE power system databases (14, 30, 57 and 118 bars) through two distinct models. The relationships between CRO parameters and the occurrence of elementary reactions was exploited, achieving better results through specific reactions. Due to problems similarity and larger scales, the software was adapted to Beasley OR-Library Set Covering (SC) problems. In the process to achieve GAPs smaller than 10% for some files, we tried out dedicated local searches, disturbance recurrence limits and stop condition changes. However, we suggest continuing to evaluate CRO method adherence to SC problem using different data structures to decrease computational times.
DOI: 10.6084/m9.figshare.19967733
title: ANALYSIS OF THE BRAZILIAN STOCK MARKET THROUGH GRAPH CENTRALITY MEASURES

description: ABSTRACT This article aims to analyze the shares that make up the Brazilian IBRX100 index, verifying which sectors had the greatest influence on the Stock Exchange in 2018, 2019, and 2020. For this purpose, the theory of graph centrality measures was used to discover the most central shares. A balance analysis of the graphs was also performed, since balanced graphs are more stable, generating a more predictable stock portfolio. This study may help investors to compose a safer stock portfolio and identify which stocks are most correlated with each other. The most central shares can aid in perceiving stock market trends.
DOI: 10.6084/m9.figshare.19967733.v1
title: ANALYSIS OF THE BRAZILIAN STOCK MARKET THROUGH GRAPH CENTRALITY MEASURES

description: ABSTRACT This article aims to analyze the shares that make up the Brazilian IBRX100 index, verifying which sectors had the greatest influence on the Stock Exchange in 2018, 2019, and 2020. For this purpose, the theory of graph centrality measures was used to discover the most central shares. A balance analysis of the graphs was also performed, since balanced graphs are more stable, generating a more predictable stock portfolio. This study may help investors to compose a safer stock portfolio and identify which stocks are most correlated with each other. The most central shares can aid in perceiving stock market trends.
DOI: 10.6084/m9.figshare.19967736
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.