The Tigris hydropower system is analyzed through an integrated operational policy. The operation algorithm is formulated in terms of non-linear programming to maximize energy production while satisfying water demands ...
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The Tigris hydropower system is analyzed through an integrated operational policy. The operation algorithm is formulated in terms of non-linear programming to maximize energy production while satisfying water demands in the basin. The system is optimized for different cases, and the effects of system modifications in terms of the reservoir volume of Ilisu Dam and the demand constraints are examined. In addition, the state of the Garzan subsystem is analyzed to explore plant utilization when optimizing the entire system operations. The results show the necessity of such an integrated operation plan to supply water demands in the basin.
This paper addresses the mobile targets covering problem by using unmanned aerial vehicles (UAVs). It is assumed that each UAV has a limited initial energy and the energy consumption is related to the UAV's altitu...
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This paper addresses the mobile targets covering problem by using unmanned aerial vehicles (UAVs). It is assumed that each UAV has a limited initial energy and the energy consumption is related to the UAV's altitude. Indeed, the higher the altitude, the larger the monitored area and the higher the energy consumption. When an UAV runs out of battery, it is replaced by a new one. The aim is to locate UAVs in order to cover the piece of plane in which the target moves by using a minimum number of UAVs. Each target has to be monitored for each instant time. The problem under consideration is mathematically represented by defining mixed integer non-linear optimization models. Heuristic procedures are defined and they are based on restricted mixed integer programming (MIP) formulation of the problem. A computational study is carried out to assess the behaviour of the proposed models and MIP-based heuristics. A comparison in terms of efficiency and effectiveness among models and heuristics is carried out.
It has been generally recognized that the product variety or product line decision is one of critical importance to marketing and product managers. Product line composition is one of the most pervasive problems that i...
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It has been generally recognized that the product variety or product line decision is one of critical importance to marketing and product managers. Product line composition is one of the most pervasive problems that includes analysis of product additions as well deletions and the degree of complementarity and substitutability among the different items within the product line. Equally important is the ordering decision which determines the order size and timing of the order for replenishing the stock of each of the products that constitute the given product line. We develop a model, OPROVAR (optimization of product variety and ordering strategy) that considers simultaneously the order quantity decision of a product and the stocking decision of a product line to maximize total profits. (C) 1998 Elsevier Science Ltd. All rights reserved.
We extend the principal sensitivity analysis results for parametric non-lieear programs with linear constraints. In particular, we obtain sufficient conditions for the existence, continuity and differentiability of a ...
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We extend the principal sensitivity analysis results for parametric non-lieear programs with linear constraints. In particular, we obtain sufficient conditions for the existence, continuity and differentiability of a locally unique perturbed local minimum. We also show that the local optimal value function is differentiable under these conditions.
A multi-objective optimization technique for the operation of an irrigation reservoir is presented in this paper. The study deals with two different objective functions (OF): the minimization of reservoir release defi...
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A multi-objective optimization technique for the operation of an irrigation reservoir is presented in this paper. The study deals with two different objective functions (OF): the minimization of reservoir release deficit from the irrigation demand (OF1) and the maximization of net benefit by the demand sector (OF2). In the first step, monthly optimization of each individual objective was performed with a deterministic non-linear programming (NLP) algorithm, that gave the lower and upper bounds for the multi-objective analysis. In the second step, multi-objective optimization was performed through the Constraint method that operates by optimising the objective function OF1, while the other (OF2) was constrained to satisfy release strategies generated by the optimization. non-dominated set of release strategies is generated by parametrically varying the bounds of the constraints obtained from the individual optimal solutions. In the third step, the interactive analytical Step method was applied to find the best compromise solution, between the two OFs, by minimizing the distance of each non-dominated solution to an ideal solution that represents the utopian optimum for both OF1 and OF2. Furthermore, the interactive approach allows to improve the performance of the reservoir in terms of compromise irrigation releases, by changing the OF values until the satisfaction of predetermined criteria fixed by the planners and decision makers. The proposed water allocation model was applied to the Pozzillo reservoir operation, that supplies the Catania Plain irrigation area (Eastern Sicily).
In this paper, we study B-spline curve interproximation with different energy forms and parametrization techniques, and present an interproximation scheme for B-spline surfaces. It shows that the energy form has a muc...
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In this paper, we study B-spline curve interproximation with different energy forms and parametrization techniques, and present an interproximation scheme for B-spline surfaces. It shows that the energy form has a much bigger impact on the generated curve than the parametrization technique. With the same energy form, different parametrization techniques generate relatively small difference on the corresponding curves. With the same parametrization technique, however, different energy forms make significant difference on the shape and smoothness of the resulting curves. Furthermore, interproximating B-spline curves generated by minimizing approximated energy forms are far from being good approximations to the optimal curves. They tend to generate flatter regions and sharper turns than curves generated by minimizing the exact energy form. The interproximation scheme for surfaces is aimed at generating a smooth surface to interpolate a grid of data which could either be a point or a region. This is achieved by minimizing a strain energy based on squared principal curvatures for bicubic B-spline surfaces. The surface interproximation process is also studied with different energy forms and parametrization techniques. The test results of the surface interproximation process also show the same conclusion as the curve interproximation process. (C) 1997 Elsevier Science Ltd.
This paper investigates the validity of a simplified equivalent reservoir representation of a multi-reservoir hydroelectric system for modelling its optimal operation for power maximization. This simplification, propo...
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This paper investigates the validity of a simplified equivalent reservoir representation of a multi-reservoir hydroelectric system for modelling its optimal operation for power maximization. This simplification, proposed by Arvanitidis and Rosing (IEEE Trans Power Appar Syst 89(2):319-325, 1970), imputes a potential energy equivalent reservoir with energy inflows and outflows. The hydroelectric system is also modelled for power maximization considering individual reservoir characteristics without simplifications. Both optimization models employed MINOS package for solution of the non-linear programming problems. A comparison between total optimized power generation over the planning horizon by the two methods shows that the equivalent reservoir is capable of producing satisfactory power estimates with less than 6% underestimation. The generation and total reservoir storage trajectories along the planning horizon obtained by equivalent reservoir method, however, presented significant discrepancies as compared to those found in the detailed modelling. This study is motivated by the fact that Brazilian generation system operations are based on the equivalent reservoir method as part of the power dispatch procedures. The potential energy equivalent reservoir is an alternative which eliminates problems with the dimensionality of state variables in a dynamic programming model.
In Australia, climate variability and the predicted impact of climate change help in making seasonal rainfall less predictable and seasonal irrigation supplies more uncertain, eroding agricultural production prospects...
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In Australia, climate variability and the predicted impact of climate change help in making seasonal rainfall less predictable and seasonal irrigation supplies more uncertain, eroding agricultural production prospects and profitability. Water allocation forecasts have economic value to irrigators for making informed cropping decisions. This study estimated the economic value of improved irrigation allocation forecasts in the Coleambally irrigation area (CIA) in southeastern Australia using a non-linear programming model. The model uses production and profit functions to estimate yield and gross margins for various water allocation levels rather than using given crop yields and gross margins. The model also captures the tactical response of improved cropping decisions made by irrigators based on water allocation announcements throughout the irrigation season. Tactical responses include changing the winter crop combinations, abandoning irrigation for a percentage of the summer crops, temporary purchase or sale of water, and deficit irrigation. The estimated economic benefit of improved seasonal water allocation forecasts to the CIA irrigators ranges from AU$1.33 ha(-1) to AU$9.58 ha(-1) (AU$1 = US$0.77). The economic analysis of water allocation forecasts shows that the potential total gross margin for the irrigators at the 100% allocation level was AU$47.6 m, assuming accurate forecast of the end-of-season allocations. A more realistic scenario generates a forecast value of AU$8.9 million reduction in the gross margin (pessimistic water allocation outlook) and AU$1.60 million in the forgone gross margin (optimistic water allocation outlook) for only 5% variation in outlook above or below the actual allocation level of 60%. This suggests that losses far exceed when water allocations are over-estimated by irrigators, as resources and inputs could be overly committed to execute the less-informed cropping plans. The knowledge benefits from forecasts are far greater at th
Over the past three decades Evolutionary Algorithms have emerged as a powerful mechanism for finding solutions to large and complex problems. A promising new evolutionary algorithm known as Differential Evolution (DE)...
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Over the past three decades Evolutionary Algorithms have emerged as a powerful mechanism for finding solutions to large and complex problems. A promising new evolutionary algorithm known as Differential Evolution (DE) was recently introduced and has garnered significant attention in the research literature. This paper introduces a modification to DE that enhances its rate of convergence without compromising solution quality. DE was recently shown to outperform several well-known stochastic optimization methods on an extensive set of test problems. Our Modified Differential Evolution (MDE) algorithm utilizes selection pressure to develop offspring that are more fit to survive than those generated from purely random operators. We demonstrate that MDE requires less computational effort to locate global optimal solutions to well-known test problems in the continuous domain. (c) 2004 Elsevier Ltd. All rights reserved.
Biomethane, a renewable gas (RG), is gaining popularity globally since the advocacy for greenhouse gas (GHG) emission reductions. Biomethane includes upgraded biogas and upgraded landfill gas. Upgraded biogas is gener...
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Biomethane, a renewable gas (RG), is gaining popularity globally since the advocacy for greenhouse gas (GHG) emission reductions. Biomethane includes upgraded biogas and upgraded landfill gas. Upgraded biogas is generated and upgraded from biomass, for example, energy crops or agricultural waste through anaerobic digestion, while upgraded landfill gas is collected and upgraded directly from gas released from a landfill site. In Malaysia, biogas and landfill gas are usually used on site. The potential for transporting upgraded biogas for off-site utilisation through pipeline injection is yet to be explored. This paper presents economic models, spatial analysis and scenario analysis to identify an appropriate biogas supply chain to different demand: industrial area, commercial area and residential area at different pressures: 20 psig, 4.3 psig and 0.43 psig through injection into the natural gas grid. The trade-off between the compression pressure and the distance of transportation is assessed and the results reveal that injection of biogas into the natural gas gate for industrial usage at 20 psig is the best option, with associated costs of 2.07 x 10(9) MYR/y. The cost is higher than supplying the demand with natural gas, which has an annual cost of MYR 985.87 M. Therefore, incentives for sales of biogas and turning the environmental liability of methane gas emitted from the landfill into an economic opportunity is essential so that the biogas can be sold at a competitive price as natural gas. The methodology can be applied at regional and country level to support policy makers to define and implement a strategy for future landfill gas to be injected into the natural gas grid in order achieve the country's renewable energy target of 30% in 2025. (C) 2017 Elsevier Ltd. All rights reserved.
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