A priori reformulations for joint rolling-horizon scheduling of materials processing and lot-sizing problem

In many production processes, a key material is prepared and then transformed into different final products. The lot sizing decisions concern not only the production of final products, but also that of material preparation in order to take account of their sequence-dependent setup costs and times. The amount of research in recent years indicates the relevance of this problem in various industrial settings. In this paper, facility location reformulation and strengthening constraints are newly applied to a previous lot-sizing model in order to improve solution quality and computing time. Three alternative metaheuristics are used to fix the setup variables, resulting in much improved performance over previous research, especially regarding the use of the metaheuristics for larger instances. © 2013 Elsevier Ltd. All rights reserved.

Technology and work organization in Latin American motor vehicle industries

Includes bibliography

Study of problems related with the establishment of motor-vehicle industries in developing countries

Information Paper, No 12

Case study on the manufacture of pistons and other motor-vehicle parts in Mexico

Information Paper, No 15

Cost-volume ratios in the motor-vehicle industry; final assembly

Information Paper, No 19

Production lot sizing and scheduling with non-triangular sequence-dependent setup times

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The association of chlorhexidine digluconate and calcium chloride to use as vehicle of a silicate calcium-based cement

Objective: The purpose of this study was to evaluate the influence of the addition of 2% chlorhexidine digluconate (CHX) associated with 5% calcium chloride (CaCl2 ) on antimicrobial activity, setting time, pH and calcium release of gray mineral trioxide aggregate (GMTA). Materials and Methods: GMTA powder was mixed with water, 2% CHX alone or 2% CHX combined with 5% CaCl2 . Antimicrobial activity was determined against Enterococcus faecalis (ATCC 29212) strains by agar diffusion test. Data obtained were submitted to kruskal wallis tests. Analysis of the setting time was evaluated by American society for testing and materials C266-03 requirements. The pH and calcium release analysis were evaluated, in 24 h, 7, 14 and 28 days using pH meter equipment and atomic absorption spectrophotometer, respectively. Data obtained were analyzed by ANOVA, in 5% significance level. Results: Significant differences were seen (P < 0.01) among the zones of bacterial growth inhibition produced by 5% CaCl2 + 2% CHX combination against E. faecalis when compared with water (P < 0.05). Regarding the setting time, that combination had the shortest setting time (P < 0.05). All associations were alkaline and released calcium. No statistical difference was observed between the experimental groups at the different periods of analysis (P > 0.05). Conclusion: Combination of 5% CaCl2 + 2% CHX reduced the setting time and enhanced the antimicrobial activity of GMTA without changing the pH and calcium release.

An MILP model for the plug-in electric vehicle charging coordination problem in electrical distribution systems

A new mixed-integer linear programming (MILP) model is proposed to represent the plug-in electric vehicles (PEVs) charging coordination problem in electrical distribution systems. The proposed model defines the optimal charging schedule for each division of the considered period of time that minimizes the total energy costs. Moreover, priority charging criteria is taken into account. The steady-state operation of the electrical distribution system, as well as the PEV batteries charging is mathematically represented; furthermore, constraints related to limits of voltage, current and power generation are included. The proposed mathematical model was applied in an electrical distribution system used in the specialized literature and the results show that the model can be used in the solution of the PEVs charging problem.

Mutagenicity profile of atmospheric particulate matter in a small urban center subjected to airborne emission from vehicle traffic and sugar cane burning

Atmospheric particulate matter (PM) is genotoxic and recently was classified as carcinogenic to humans by the International Agency for Research on Cancer. PM chemical composition varies depending on source and atmospheric conditions. The Salmonella/microsome assay is the most used mutagenicity test and can identify the major chemical classes responsible for observed mutagenicity. The objective of this work was to characterize the mutagenicity of PM samples from a countryside city, Limeira, Brazil, which is influenced by heavy traffic and sugar cane biomass burning. Six samples of total PM were collected. Air mass backward trajectories were calculated. Organic extracts were assayed using the Salmonella/microsome microsuspension mutagenicity assay using TA98, YG1041, and TA1538, with and without metabolic activation (S9). YG1041 was the most sensitive strain and mutagenicity reached 9,700 revertants per m(3) without metabolic activation. Potency for TA1538 was higher than TA98, indicating that this strain should be considered in air mutagenicity studies. The increased response to YG1041 relative to TA98, and the decreased response with S9, suggests that nitroaromatics are the major contributors. Limeira is among the most mutagenic cities in the world. High mutagenicity in Limeira seems to occur when the air mass from the area of sugarcane production is mixed with air from the region impacted by anthropogenic activities such as traffic. An increase in the formation of nitro-polycyclic aromatic hydrocarbons may result from longer contact time between the aromatic compounds and the atmosphere with high NOx and ozone concentration, although more studies are required to confirm this hypothesis. Environ. Mol. Mutagen., 2015. © 2015 Wiley Periodicals, Inc.

Projeto de controlador gain scheduling usando realimentação derivativa via LMI

Pós-graduação em Engenharia Elétrica - FEIS

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Dynamic Lightpath Scheduling in Next-Generation WDM Optical Networks

Lightpath scheduling is an important capability in next-generation wavelength-division multiplexing (WDM) optical networks to reserve resources in advance for a specified time period while provisioning end-to-end lightpaths. In this study, we propose an approach to support dynamic lightpath scheduling in such networks. To minimize blocking probability in a network that accommodates dynamic scheduled lightpath demands (DSLDs), resource allocation should be optimized in a dynamic manner. However, for the network users who desire deterministic services, resources must be reserved in advance and guaranteed for future use. These two objectives may be mutually incompatible. Therefore, we propose a two-phase dynamic lightpath scheduling approach to tackle this issue. The first phase is the deterministic lightpath scheduling phase. When a lightpath request arrives, the network control plane schedules a path with guaranteed resources so that the user can get a quick response with the deterministic lightpath schedule. The second phase is the lightpath re-optimization phase, in which the network control plane re-provisions some already scheduled lightpaths. Experimental results show that our proposed two-phase dynamic lightpath scheduling approach can greatly reduce WDM network blocking.

A Two-phase Approach for Dynamic Lightpath Scheduling in WDM Optical Networks

Lightpath scheduling is an important capability in next-generation wavelength-division multiplexing (WDM) optical networks to reserve resources in advance for a specified time period while provisioning end-to-end lightpaths. In a dynamic environment, the end user requests for dynamic scheduled lightpath demands (D-SLDs) need to be serviced without the knowledge of future requests. Even though the starting time of the request may be hours or days from the current time, the end-user however expects a quick response as to whether the request could be satisfied. We propose a two-phase approach to dynamically schedule and provision D-SLDs. In the first phase, termed the deterministic lightpath scheduling phase, upon arrival of a lightpath request, the network control plane schedules a path with guaranteed resources so that the user can get a quick response with a deterministic lightpath schedule. In the second phase, termed the lightpath re-optimization phase, we re-provision some already scheduled lightpaths to re-optimize for improving network performance. We study two reoptimization scenarios to reallocate network resources while maintaining the existing lightpath schedules. Experimental results show that our proposed two-phase dynamic lightpath scheduling approach can greatly reduce network blocking.