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Alvarez-Miranda, E., Pereira, J., & Vila, M. (2023). Analysis of the simple assembly line balancing problem complexity. Comput. Oper. Res., 159, 106323.
Abstract: The simple assembly line balancing problem (SALBP) involves the determination of the assignment of elementary assembly operations to the workstations of the assembly line for the manufacture of a final product, with the objective of maximising assembly efficiency. In addition to its practicality, the SALBP can be considered as an extension of the bin packing problem (BPP) to account for the precedence relations between items. These constraints introduce an ordering component to the problem, which increases the complexity of SALBP resolution. However, previous studies indicated that precedence constraints do not play an important role in the capacity of state-of-the-art procedures to solve benchmark instances to optimality. In this study, we analysed the influences of different features of an SALBP instance on the performance of state-of-the-art solution methods for the abovementioned problem. First, we provide an alternative proof of complexity for the SALBP that uses precedence constraints to demonstrate its non-deterministic polynomial time (NP)-complete status, followed by a new set of benchmark instances directed towards an empirical analysis of the different features of SALBP instances. The experimental results revealed that the packing features of the SALBP are a major source of the perceived difficulty for any instance; however, precedence constraints play a role in the performance of these solution procedures. Specifically, the number of precedence constraints plays an important role in the results obtained from state-of-the-art methods. In addition to the analysis, certain issues that were identified in the publicly available implementations of the state-of-the-art method for resolving this problem were addressed in this study.
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Bernales, A., Reus, L., & Valdenegro, V. (2022). Speculative bubbles under supply constraints, background risk and investment fraud in the art market. J. Corp. Financ., 77, 101746.
Abstract: We examine the unexplored effects on art markets of artist death (asset supply constraints), collectors' wealth (background risk) and forgery risk (risk of investment fraud), under short-sale constraints and risk aversion. Speculative bubbles emerge and have the form of an option strangle (a put option and a call option), in which strike prices are affected by art supply constraints and the association of the artworks' emotional value with both collectors' wealth and forgery, while the options' underlying asset is the stochastic heterogeneous beliefs of agents. We show that speculative bubbles increase with four elements: art supply constraints; a more negative correlation between collectors' wealth and the artworks' emotional value; a more positive relationship between forgery and the artworks' emotional value; and more heterogeneous beliefs. These four sources of speculation increase the expected turnover rate; however, they also augment the variance of speculative bubbles, which generates price discounts (i.e. risk premiums) for holding artworks. Consequently, the net impact of speculation is not necessarily increased art prices. This study not only contributes to the art market literature, but also to studies about speculative bubbles in other financial markets under heterogeneous beliefs, short-sale constraints and risk-averse investors, since we additionally consider the simultaneous effect of asset supply constraints, investors' background risk and the risk of investment fraud.
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Bertossi, L. (2021). Specifying and computing causes for query answers in databases via database repairs and repair-programs. Knowl. Inf. Syst., 63, 199–231.
Abstract: There is a recently established correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints. In this work, answer-set programs that specify database repairs are used as a basis for solving computational and reasoning problems around causality in databases, including causal responsibility. Furthermore, causes are introduced also at the attribute level by appealing to an attribute-based repair semantics that uses null values. Corresponding repair-programs are introduced, and used as a basis for computation and reasoning about attribute-level causes. The answer-set programs are extended in order to capture causality under integrity constraints.
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Bertossi, L. (2022). Declarative Approaches to Counterfactual Explanations for Classification. Theory Pract. Log. Program., Early Access.
Abstract: We propose answer-set programs that specify and compute counterfactual interventions on entities that are input on a classification model. In relation to the outcome of the model, the resulting counterfactual entities serve as a basis for the definition and computation of causality-based explanation scores for the feature values in the entity under classification, namely responsibility scores. The approach and the programs can be applied with black-box models, and also with models that can be specified as logic programs, such as rule-based classifiers. The main focus of this study is on the specification and computation of best counterfactual entities, that is, those that lead to maximum responsibility scores. From them one can read off the explanations as maximum responsibility feature values in the original entity. We also extend the programs to bring into the picture semantic or domain knowledge. We show how the approach could be extended by means of probabilistic methods, and how the underlying probability distributions could be modified through the use of constraints. Several examples of programs written in the syntax of the DLV ASP-solver, and run with it, are shown.
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Caniupan, M., Bravo, L., & Hurtado, C. A. (2012). Repairing inconsistent dimensions in data warehouses. Data Knowl. Eng., 79-80, 17–39.
Abstract: A dimension in a data warehouse (DW) is a set of elements connected by a hierarchical relationship. The elements are used to view summaries of data at different levels of abstraction. In order to support an efficient processing of such summaries, a dimension is usually required to satisfy different classes of integrity constraints. In scenarios where the constraints properly capture the semantics of the DW data, but they are not satisfied by the dimension, the problem of repairing (correcting) the dimension arises. In this paper, we study the problem of repairing a dimension in the context of two main classes of integrity constraints: strictness and covering constraints. We introduce the notion of minimal repair of a dimension: a new dimension that is consistent with respect to the set of integrity constraints, which is obtained by applying a minimal number of updates to the original dimension. We study the complexity of obtaining minimal repairs, and show how they can be characterized using Datalog programs with weak constraints under the stable model semantics. (c) 2012 Elsevier B.V. All rights reserved.
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Cho, A. D., Carrasco, R. A., & Ruz, G. A. (2022). Improving Prescriptive Maintenance by Incorporating Post-Prognostic Information Through Chance Constraints. IEEE Access, 10, 55924–55932.
Abstract: Maintenance is one of the critical areas in operations in which a careful balance between preventive costs and the effect of failures is required. Thanks to the increasing data availability, decision-makers can now use models to better estimate, evaluate, and achieve this balance. This work presents a maintenance scheduling model which considers prognostic information provided by a predictive system. In particular, we developed a prescriptive maintenance system based on run-to-failure signal segmentation and a Long Short Term Memory (LSTM) neural network. The LSTM network returns the prediction of the remaining useful life when a fault is present in a component. We incorporate such predictions and their inherent errors in a decision support system based on a stochastic optimization model, incorporating them via chance constraints. These constraints control the number of failed components and consider the physical distance between them to reduce sparsity and minimize the total maintenance cost. We show that this approach can compute solutions for relatively large instances in reasonable computational time through experimental results. Furthermore, the decision-maker can identify the correct operating point depending on the balance between costs and failure probability.
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Fernandez, M., Munoz, F. D., & Moreno, R. (2020). Analysis of imperfect competition in natural gas supply contracts for electric power generation: A closed-loop approach. Energy Econ., 87, 15 pp.
Abstract: The supply of natural gas is generally based on contracts that are signed prior to the use of this fuel for power generation. Scarcity of natural gas in systems where a share of electricity demand is supplied with gas turbines does not necessarily imply demand rationing, because most gas turbines can still operate with diesel when natural gas is not available. However, scarcity conditions can lead to electricity price spikes, with welfare effects for consumers and generation firms. We develop a closed-loop equilibrium model to evaluate if generation firms have incentives to contract or import the socially-optimal volumes of natural gas to generate electricity. We consider a perfectly-competitive electricity market, where all firms act as price-takers in the short term, but assume that only a small number of firms own gas turbines and procure natural gas from, for instance, foreign suppliers in liquefied form. We illustrate an application of our model using a network reduction of the electric power system in Chile, considering two strategic firms that make annual decisions about natural gas imports in discrete quantities. We also assume that strategic firms compete in the electricity market with a set of competitive firms do not make strategic decisions about natural gas imports (i.e., a competitive fringe). Our results indicate that strategic firms could have incentives to sign natural gas contracts for volumes that are much lower than the socially-optimal ones, which leads to supernormal profits for these firms in the electricity market. Yet, this effect is rather sensitive to the price of natural gas. A high price of natural gas eliminates the incentives of generation firms to exercise market power through natural gas contracts. (C) 2020 Elsevier B.V. All rights reserved.
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Osorio-Valenzuela, L., Pereira, J., Quezada, F., & Vasquez, O. C. (2019). Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints. Appl. Math. Model., 74, 512–527.
Abstract: In this paper, we consider a parallel machine scheduling problem in which machines have a limited workload capacity and jobs have deadlines and release dates. The problem is motivated by the operation of energy storage management systems for microgrids under emergency conditions and generalizes some problems that have already been studied in the literature for their theoretical value. In this work, we propose heuristic and exact algorithms to solve the problem. The heuristics are adaptations of classical bin packing heuristics in which additional conditions on the feasibility of a solution are imposed, whereas the exact method is a branch-and-price approach. The results show that the branch-andprice approach is able to optimally solve random instances with up to 250 jobs within a time limit of one hour, while the heuristic procedures provide near optimal solution within reduced running times. Finally, we also provide additional complexity results for a special case of the problem. (C) 2019 Elsevier Inc. All rights reserved.
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Pereira, J. (2016). Procedures for the bin packing problem with precedence constraints. Eur. J. Oper. Res., 250(3), 794–806.
Abstract: The bin packing problem with precedence constraints (BPP-P) is a recently proposed variation of the classical bin packing problem (BPP), which corresponds to a basic model featuring many underlying characteristics of several scheduling and assembly line balancing problems. The formulation builds upon the BPP by incorporating precedence constraints among items, which force successor items to be packed into later bins than their predecessors. In this paper we propose a dynamic programming based heuristic, and a modified exact enumeration procedure to solve the problem. These methods make use of several new lower bounds and dominance rules tailored for the problem in hand. The results of a computational experiment show the effectiveness of the proposed methods, which are able to close all of the previous open instances from the benchmark instance set within very reduced running times. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
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Ruiz-Rodriguez, D. A., Cieza, L. A., Casassus, S., Almendros-Abad, V., Jofre, P., Muzic, K., et al. (2022). Discovery of a Brown Dwarf with Quasi-spherical Mass Loss. Astrophys. J., 938(1), 54.
Abstract: We report the serendipitous discovery of an elliptical shell of CO associated with the faint stellar object SSTc2d J163134.1-240060 as part of the “Ophiuchus Disk Survey Employing ALMA” (ODISEA), a project aiming to study the entire population of protoplanetary disks in the Ophiuchus Molecular Cloud from 230 GHz continuum emission and (CO)-C-12 (J = 2-1), (CO)-C-13 (J = 2-1) and (CCO)-C-18 (J = 2-1) lines readable in Band 6. Remarkably, we detect a bright (CO)-C-12 elliptical shape emission of similar to 3 '' x 4 '' toward SSTc2d J163134.1-240060 without a 230 GHz continuum detection. Based on the observed near-IR spectrum taken with the Very Large Telescope (KMOS), the brightness of the source, its three-dimensional motion, and Galactic dynamic arguments, we conclude that the source is not a giant star in the distant background (>5-10 kpc) and is most likely to be a young brown dwarf in the Ophiuchus cloud, at a distance of just similar to 139 pc. This is the first report of quasi-spherical mass loss in a young brown dwarf. We suggest that the observed shell could be associated with a thermal pulse produced by the fusion of deuterium, which is not yet well understood, but for a substellar object is expected to occur during a short period of time at an age of a few Myr, in agreement with the ages of the objects in the region. Other more exotic scenarios, such as a merger with planetary companions, cannot be ruled out from the current observations.
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