Weekly Self-Scheduling, Forward Contracting, and Offering Strategy for a Producer

Within a weekly market horizon, this paper considers a power producer that sells its energy both in the pool and through weekly forward contracts. The paper provides a methodology that allows the producer to derive the self-scheduling of its production units, to select weekly forward contracts, and to obtain the offering strategy for Monday's pool. The proposed technique is based on stochastic programming and allows the producer to maximize its expected profit while controlling the risk of profit variability. A comprehensive case study is used to illustrate the characteristics of the proposed methodology. Appropriate conclusions are finally drawn.

Use of Natural Products for Post-Harvest Preservation of 'Vega' Cut Roses

Use of natural products as floral preservatives has helped to reduce the indiscriminate use of chemical products in flower preservation. In this study, we tested the ability of certain natural products to maintain the quality and to increase the commercial durability of 'Vega' cut roses. We employed a randomized factorial design with six post-harvest treatments and four evaluation dates. The following treatments were tested: 1) distilled water; 2) methyl jasmonate (350 mu M) applied in a four-hour pulse; 3) methyl jasmonate (500 mu M) spraying; 4) mint oil (100 ppm); 5) ginger oil (100 ppm); and 6) propolis (0.05%) as a maintenance solution. Flowers were kept at 20+/-2 degrees C and 67+/-3% RH. Physiological and qualitative evaluations were conducted. Natural products had a beneficial effect on the shelf life of the flowers. However, for all evaluated parameters, the methyl jasmonate spray was the most efficient treatment to maintain floral quality, resulting in less fresh-mass loss and a lower flower respiratory rate. Methyl jasmonate spray also improved the maintenance of coloration, relative water content and concentration of reducing sugars, thus extending the shelf life of roses.

Total and harvest-date yield of processing tomato cultivars

The productivity of 28 tomato cultivars was evaluated over three stages of harvest. The study was carried out during from June to December of 1999 in an open field at the experimental area of the Section of Olericulture and Aromatic Medicinal Plants, Department of Crop Production at FCAV-UNESP, Jaboticabal, SP, Brazil. The cultivars studied were H 7155, Hypeel, Andino, U 573, H 9036, IPA 6, H 9494, AG 33, Yuba, RPT 1294, AG 72, Pelmeech, Curico, Hypeel 45, RPT 1478, H 9492, H 9498, H 2710, Hitech 45, Halley, Botu 13, H 9553, U 646, NK 1570, AG 45, RPT 1095, RPT 1570, and PSX 37511. The experimental design was a randomized block design with four repetitions, with five plants per plot. Productivity was evaluated at three stages of harvest at 119, 149 and 179 days after seeding. There were no significant differences among the cultivars at the first harvest (119 days). The majority of the cultivars produced their highest yield at the second harvest; the most productive cultivars were Curicó and AG 72, which yielded 4.69 and 4.67 kg/plant, respectively, although they did not differ statistically from the cultivars Hypeel 45 (4.35 kg/plant) and H 9498 (4.16 kg/plant). Yields of the cultivars Andino and H 9494 were evenly distributed between the second and third harvests. At the third harvest, cultivar IPA 6 had the highest yield (2.9 kg/plant) and was statistically different from all other cultivars except H 9036 (2.34 kg). These two cultivars had the most delayed and concentrated maturity, making them suitable for mechanical harvesting, although at a later time. Cultivar AG 72 had the greatest total yield (5.76 kg/plant), but it was not statistically different from cultivars Hypeel 45 (5.43 kg), Curico (4.17 kg), H 9498 (4.83 kg), H 7155 (4.58 kg) and Halley (4.55 kg). All of the cultivars, with the exception of cultivars H 9036, IPA 6, Andino and H 9494 showed in the second harvest concentrated maturity, making it suitable for mechanical harvesting.

Lot sizing and furnace scheduling in small foundries

A lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (1) the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry's own practice. © 2006 Elsevier Ltd. All rights reserved.

Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: A comparison study

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

Evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem

This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

A nonlinear model for the long-term hydro-thermal generation scheduling problem over multiple areas with transmission constraints

This paper presents a nonlinear model with individual representation of plants for the centralized long-term hydrothermal scheduling problem over multiple areas. In addition to common aspects of long-term scheduling, this model takes transmission constraints into account. The ability to optimize hydropower exchange among multiple areas is important because it enables further minimization of complementary thermal generation costs. Also, by considering transmission constraints for long-term scheduling, a more precise coupling with shorter horizon schedules can be expected. This is an important characteristic from both operational and economic viewpoints. The proposed model is solved by a sequential quadratic programming approach in the form of a prototype system for different case studies. An analysis of the benefits provided by the model is also presented. ©2009 IEEE.

Simulation of computational grids scheduling politics

Computational grids allow users to share resources of distributed machines, even if those machines belong to different corporations. The scheduling of applications must be performed aiming at performance goals, and focusing on choose which processes can have access to specif resources, and which resources. In this article we discuss aspects of scheduling of application in grid computing environment. We also present a tool for scheduling simulation along with test scenarios and results.

Optimal energy generation with biomass of sugarcane harvest

The aim of this work is the application of the Interior Point and Branch and Bound methods in multiobjective optimization models related to sugarcane harvest residual biomass. These methods showed their viability to help on choosing the sugarcane planting varieties, searching to optimize cost and energy balance of harvest residual biomass, which have conflitant objectives. These methods provide satisfactory results, with fair computing performance and reliable and consistent solutions to the analyzed models. © 2011 IEEE.

Tabu search to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem

This paper proposes a tabu search approach to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). It is a real-world problem, often found in soft drink companies, where the production process has two integrated levels with decisions concerning raw material storage and soft drink bottling. Lot sizing and scheduling of raw materials in tanks and products in bottling lines must be simultaneously determined. Real data provided by a soft drink company is used to make comparisons with a previous genetic algorithm. Computational results have demonstrated that tabu search outperformed genetic algorithm in all instances. Copyright 2011 ACM.

Strategies to model scheduling decisions to plan the soft drink production process

In this paper we present a mixed integer model that integrates lot sizing and lot scheduling decisions for the production planning of a soft drink company. The main contribution of the paper is to present a model that differ from others in the literature for the constraints related to the scheduling decisions. The proposed strategy is compared to other strategies presented in the literature.

Pre-harvest sugarcane burning: Determination of emission factors through laboratory measurements

Sugarcane is an important crop for the Brazilian economy and roughly 50% of its production is used to produce ethanol. However, the common practice of pre-harvest burning of sugarcane straw emits particulate material, greenhouse gases, and tropospheric ozone precursors to the atmosphere. Even with policies to eliminate the practice of pre-harvest sugarcane burning in the near future, there is still significant environmental damage. Thus, the generation of reliable inventories of emissions due to this activity is crucial in order to assess their environmental impact. Nevertheless, the official Brazilian emissions inventory does not presently include the contribution from pre-harvest sugarcane burning. In this context, this work aims to determine sugarcane straw burning emission factors for some trace gases and particulate material smaller than 2.5μm in the laboratory. Excess mixing ratios for CO2, CO, NOX, UHC (unburned hydrocarbons), and PM2.5 were measured, allowing the estimation of their respective emission factors. Average estimated values for emission factors (g kg-1 of burned dry biomass) were 1,303 ± 218 for CO2, 65 ± 14 for CO, 1.5 ± 0.4 for NOX, 16 ± 6 for UHC, and 2.6 ± 1.6 for PM2.5. These emission factors can be used to generate more realistic emission inventories and therefore improve the results of air quality models. © 2012 by the authors; licensee MDPI, Basel, Switzerland.

Analysis of ensemble models in the medium term hydropower scheduling

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

Transaction scheduling using dynamic conflict avoidance

Software transaction memory (STM) systems have been used as an approach to improve performance, by allowing the concurrent execution of atomic blocks. However, under high-contention workloads, STM-based systems can considerably degrade performance, as transaction conflict rate increases. Contention management policies have been used as a way to select which transaction to abort when a conflict occurs. In general, contention managers are not capable of avoiding conflicts, as they can only select which transaction to abort and the moment it should restart. Since contention managers act only after a conflict is detected, it becomes harder to effectively increase transaction throughput. More proactive approaches have emerged, aiming at predicting when a transaction is likely to abort, postponing its execution. Nevertheless, most of the proposed proactive techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction to run. This article proposes LUTS, a lightweight user-level transaction scheduler. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. We discuss LUTS design and propose a dynamic conflict-avoidance heuristic built around its scheduling capabilities. Experimental results, conducted with the STAMP and STMBench7 benchmark suites, running on TinySTM and SwissTM, show how our conflict-avoidance heuristic can effectively improve STM performance on high contention applications. © 2012 Springer Science+Business Media, LLC.

Structural changes in soybean seed coat due to harvest time and storage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)