Resumo em Inglês:

ABSTRACT The one-dimensional skiving stock problem is a combinatorial optimization problem being of high relevance whenever an efficient and sustainable utilization of given resources is intended. In the classical formulation, a given supply of (small) item lengths has to be used to build as many large objects (specified by some target length) as possible. For this 𝒩𝒫-hard (discrete) optimization problem, we investigate the quality of the continuous relaxation by considering the additive integrality gap, i.e., the difference between the optimal values of the integer problem and its LP relaxation. In a first step, we derive an improved upper bound for the gap by focusing on the concept of residual instances. Moreover, we show how further upper bounds can be obtained if all problem-specific input data are considered. Additionally, we constructively prove the integer round-down property for two new classes of instances, and introduce several construction principles to obtain gaps greater than or equal to one.

Resumo em Inglês:

ABSTRACT We address the problem of expected cost minimization of meeting the uncertain fuel demand during a time planning horizon, where supply is provided by selecting discrete shipments with lead times. Due to uncertainty and the passage of time, corrective actions can be taken such as cancellation and postponement on supply of shipments with associated costs and delays. This problem is modeled as a stochastic multi-stage capacitated discrete lot-sizing problem with lead times. Computational experiments were performed on the resolution of various instances of the model for four information structures of uncertainty. The experimental optimal values and stochastic rating measures obtained show the validity and interest of the stochastic model, as well as the benefits that can be obtained with respect to a deterministic variant of the model that considers average demand.

Resumo em Inglês:

ABSTRACT This study explores the self-fulfilling dynamic between sovereign debt risk and rational choices of neutral, risk-seeking and risk-averse investors, with implications to the systemic risk emergence. The agent-based model parameterization includes investment strategy (randomly selected assets, stock exchange participation, economic segment, and technical analysis), portfolio rebalance period, and stop gain/loss option. We use Brazilian markets data from 2006 to 2017 to simulate stochastic distributions of investments by a set of 3,000 agents in both stages of model verification and validation (robustness check). Using the Capital Asset Pricing Model, we confirmed our proposition that the optimal rational risk attitude (less risk appetite) constitutes a trigger for the self-fulfilling dynamic, having its foundation on government securities yield and in the debt dynamics. This finding is contrary to the equity premium puzzle in the Brazilian case. The findings have implications to policymakers regarding systemic risk issues, among other public policies.

Resumo em Inglês:

ABSTRACT In the context of a heterogeneous fleet, the single-depot Vehicle Scheduling Problem is known as the Vehicle Type Scheduling Problem (VTSP). In this paper, we extend a VTSP model proposed in the literature to enable timetabling flexibility. Two strategies were developed to promote flexibility: aggregated trips and time windows. The former allows to aggregate two or more trips, occurring close in time, into a single one through the use of larger vehicle types, while the latter allows shifting the departure time of scheduled trips backward in few minutes. Both approaches were tested on generated instances that simulate the traffic behavior of a Brazilian city, where clock-face departure pattern is not required and demand peak times occur. We verified significant savings in the daily operation of the public transportation service with acceptable impact on passengers’ experience.

Resumo em Inglês:

ABSTRACT The scheduling of jobs over a single machine with sequence dependent setups is a classical problem setting that appears in many practical applications in production planning and logistics. In this work, we analyze six mixed-integer formulation paradigms for this classical context considering release dates and two objective functions: the total weighted completion time and the total weighted tardiness. For each paradigm, we present and discuss a MIP formulation, introducing in some cases new constraints to improve performance. A dominance hierarchy in terms of strength of their linear relaxations bounds is developed. We report extensive computational experiments on a variety of instances to capture several aspects of practical situations, allowing a comparison regarding size, linear relaxation and overall performance. Based on the results, discussions and recommendations are made for the considered problems.

Resumo em Inglês:

ABSTRACT This paper describes a study of the dispatch planning/scheduling process for inbound containers handled with a reach stacker. Client container pickup is scheduled at least one day in advance for one of six two-hour time windows (six five-container-high stacks per time window) on a given day. A buffer area is available for the containers to be moved in when clients are being served. The aim of this study was to determine the conditions required to ensure that all the containers are dispatched within the scheduled time window and so meet the clients’ requirements. To this end, the performance indicators were identified and compared using simulations as an analytical tool. The results indicate that the shortest-processing-time (SPT) queueing discipline is preferable to the first-come-first-served (FCFS) discipline and that client arrivals can usefully be restricted to periods shorter than two hours in order to meet container-dispatch and service-quality objectives.

Resumo em Inglês:

ABSTRACT In this paper, a new software for Statistical Process Control (SPC) is proposed. The system, the so-called CEP Online, was developed based on statistical computing resources of well-known free softwares, such as HTML, PHP, R and MySQL under an online server with operating system Linux Ubuntu. The main uni and multivariate SPC tools are available for monitoring and evaluation of manufacturing and non-manufacturing production processes over time. Some advantages of the new software are: (i) low operational cost, since it is cloud-based, only needing a computer connected to the Internet; (ii) easy to use with great interaction with the user; (iii) it does not require investment in any specific hardware or software; (iv) real time reports generation on process condition monitoring and process capability. Thus, the CEP Online offers for SPC practitioners fast, efficient and accurate SPC procedures. Therefore, CEP Online becomes an important resource for those who have no access to non-free softwares, such as SAS, SPSS, Minitab and STATISTICA. To the best of our knowledge, the CEP Online is unique with respect to its characteristics.

Resumo em Inglês:

ABSTRACT In this paper we analyzed the probabilities of transitions of state between Ibovespa and Dow Jones indexes using High-order Multivariate Markov Chain. While the stock market may be profitable, the existence of risks can lead to large losses. A mathematical model capable of considering different sources can aid in decision making. This model can work with stochastic data, causing different databases to be transformed into transitional matrices between states. For this, a set of a daily variation data were used between January 2008 and March 2018. Through this application, it was possible to show an interaction between the indexes and that the highest frequency of events was of the variation of -0.49 to 0.5% in Dow Jones to -0.49 to 0.5% in Ibovespa, with 428 cases, and the probability of this situation occurring again, of Dow Jones at time t to Ibovespa at time t+2, is 27.21%. Empirical results suggest that this application can help investors make decisions based on transition probabilities.