This project aims to model the wastewater regulation problem as a bilevel optimization problem. Due to human activities such as industry, agriculture, and domestic use, many bodies of water have been affected by pollu...
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This project aims to model the wastewater regulation problem as a bilevel optimization problem. Due to human activities such as industry, agriculture, and domestic use, many bodies of water have been affected by pollution. To remedy the problem of water quality Environmental Protection Agencies use environmental penalty functions. This enforces managers of wastewater treatment plants to find treatment strategies that meet water quality standards before discharging pollution to the environment. In the case of shallow bodies of water, the behavior of the wastewater dispersion is governed by the Navier-Stokes equation;therefore, the objective functions of the decision-makers have a nonlinear behavior relative to a leader-follower dynamic. To find the optimal penalty function we construct the emission concentration system solution and define the wastewater regulation problem as a bilevel optimization problem. The aim of this paper is threefold: First, it formulates the wastewater regulation problem as a bilevel optimization problem;second, it provides theoretical insight when the problem is reformulated to a single-level formulation using a Karush-Kuhn-Tucker condition approach;third, it develops discretization techniques that allow finding numerical solutions of the location of the wastewater regulation problem.
In this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions i...
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In this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.
Purpose The purpose of this paper is to study the relationship among environmental degradation, energy use and economic growth, thus lending a voice to testing the relevance, or otherwise, of the environmental Kuznets...
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Purpose The purpose of this paper is to study the relationship among environmental degradation, energy use and economic growth, thus lending a voice to testing the relevance, or otherwise, of the environmental Kuznets curve (EKC) hypothesis in Nigeria. Design/methodology/approach The authors rely on the secondary data obtained from World Bank's World Development Indicators for Nigeria, between 1981 and 2014. The non-linear autoregressive distributed lag (ARDL) technique is used after examining the unit root properties - using the augmented Dickey-Fuller and Phillips-Perron methods - and the long-run relationship - using the ARDL bounds approach to estimate the asymmetries in the effects of economic growth on the environment. Findings The findings of this study uphold the relevance of the EKC hypothesis in Nigeria, as the growth of GDP first reduces the environmental quality but raises it over time. Furthermore, the use of energy is found to deteriorate environmental quality, given that CO2 rises by 0.002% for a unit increase in the consumption of energy in Nigeria. Research limitations/implications A limitation to this research is the data coverage, which is just between 1981 and 2014, based on availability. One other limitation is the use of electric power consumption as a proxy for energy use (because of the difficulty in obtaining accurate data on energy consumption in Nigeria). Future research should, therefore, test different other proxies, to either agree with the findings or justify any deviation therefrom. Also, the use of up-to-date data is recommended as an improvement to this study, while a non-linear technique should be used on studies involving the panel of countries. Originality/value Many studies have examined this relationship by simply taking the square of GDP as a measure of its non-linear effect on the environment. The authors are one of the first who consider the asymmetric effect of economic growth on the environment through the non-linear ARDL
The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operational schedule. Deep reinforcement...
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The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms arise as a promising solution due to their data-driven and model-free features. However, current DRL algorithms fail to enforce rigorous operational constraints (e.g., power balance, ramping up or down constraints) limiting their implementation in real systems. To overcome this, in this paper, a DRL algorithm (namely MIP-DQN) is proposed, capable of strictly enforcing all operational constraints in the action space, ensuring the feasibility of the defined schedule in real-time operation. This is done by leveraging recent optimization advances for deep neural networks (DNNs) that allow their representation as a MIP formulation, enabling further consideration of any action space constraints. Comprehensive numerical simulations show that the proposed algorithm outperforms existing state-of-the-art DRL algorithms, obtaining a lower error when compared with the optimal global solution (upper boundary) obtained after solving a mathematical programming formulation with perfect forecast information;while strictly enforcing all operational constraints (even in unseen test days).
Brick-and-mortar retailers are struggling to compete with online retailers, who increasingly use customer-generated data to provide highly customized experiences for their patrons to drive impulse purchases. Although ...
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Brick-and-mortar retailers are struggling to compete with online retailers, who increasingly use customer-generated data to provide highly customized experiences for their patrons to drive impulse purchases. Although brick-and-mortar retailers cannot offer such customization, they must identify innovative ways to transform their own point-of-sale transaction data into increased customer impulse buying. We propose a shelf allocation-relocation scheme for rearranging storewide product allocations over time to maximize impulse buying behavior. The proposed method provides a roadmap for optimally allocating shelf space when routine rearrangements of a retail store take place per store policy. To the best of our knowledge, this represents one of the first periodic storewide rearrangement studies to use customer tendencies with the current shelf arrangement as the basis for the subsequent one. We also introduce a novel approach for incorporating past transaction data insights of cross-selling elasticity into the Shelf Space Allocation Problem (SSAP) to encourage long-term new business creation through impulse purchases. The method applies insights from association rule mining to group highly affine and profitable product pairs, optimize the assignment of departments to store aisles, and determine the optimal within-aisle space allocations for the products of each department. Our major finding is that, based on the potential of generating multiple forms of impulse purchasing (visibility-driven purchasing, present-shelf impulse, and past-aisle impulse), our strategic rearrangement technique consistently outperforms visually rearranging shelf space allocations and several existing allocation techniques that utilize multi-level association rule mining, while, in many instances, exceeding the profit potential of a more traditional unchanged (one-time optimal) shelf space arrangement, depending on the nature of a retailer's target market. Our results also high-light the importa
The towed frequency-domain electromagnetic (TFEM) detection system is an effective tool for detecting underground anomalous targets. To improve detection efficiency and measurement accuracy for specific depth targets,...
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The towed frequency-domain electromagnetic (TFEM) detection system is an effective tool for detecting underground anomalous targets. To improve detection efficiency and measurement accuracy for specific depth targets, the depth-focused waveform with multiple probing frequencies closely spaced in the spectrum was introduced. However, the transmitting coil impedance severely suppresses the transmission energy of the excitation signal, which will reduce the transmission efficiency and signal-to-noise ratio (SNR). To solve this problem, a novel optimization method for the traditional depth-focused transmitting system is proposed to simultaneously improve the transmission energy of multiple probing frequencies in the effective band. First, the traditional depth-focused waveform is optimized with the objectives of matching the desired spectrum and maximizing the transmission energy by the nonlinear programming approach, which provides closer spectral energy between the probing frequencies and less undesired harmonic pollution. Then, we design the corresponding broadband resonant compensator based on an improved LC series resonant circuit to simultaneously enhance multiple spectral amplitudes in the effective band. Furthermore, the enhancement effect of compensator parameters on the depth-focused waveforms is analyzed, and the design principle of compensator parameters is provided. Finally, the feasibility of the proposed optimization method is verified by simulation and laboratory experiments and the actual limitation of the novel scheme is discussed in detail.
The authors consider the optimization problem of layout of spherical voids in three-dimensional domains bounded by cylindrical and spherical surfaces and planes. The problem is reduced to arranging spherical objects i...
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The authors consider the optimization problem of layout of spherical voids in three-dimensional domains bounded by cylindrical and spherical surfaces and planes. The problem is reduced to arranging spherical objects in a composite container, with regard for the constraints on their "sparseness" and balance conditions (location of the gravity center of the system). A mathematical model in the form of a nonlinear programming problem is constructed. A method of fast search for feasible solutions based on the balanced homothetic transformations of 3D objects and methods of finding locally optimal solutions using the decomposition algorithm and r-algorithm are proposed. The results of numerical experiments are provided.
This paper presents in-depth comparative analyses of nonlinear nonconvex programming (NLNCP) and second-order conic programming (SOCP) models to solve the optimal power flow problem in electric power systems. For comp...
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This paper presents in-depth comparative analyses of nonlinear nonconvex programming (NLNCP) and second-order conic programming (SOCP) models to solve the optimal power flow problem in electric power systems. For comparative purposes, two objective functions are considered (1) minimization of the active power generation costs and (2) minimization of the active power losses in the transmission branches. The robustness and precision of the NLNCP and SOCP models are analyzed and discussed considering the feasibility of the active and reactive power balance constraints and the values of the objective functions. The obtained operational points are verified through the solution of the AC power flow problem using the Newton-Raphson method. For both models, numerical experiments show consistent active power dispatch;however, limit violations in the reactive power generation limits are observed in the solutions obtained by the SOCP model. To address this issue, two variations in the formulation of the SOCP model are proposed (1) considering a penalty factor in the generation of reactive energy and (2) considering a minimum resistance in branches of the power system that have resistance equal to zero. The solution of these modified SOCP models can eliminate or significantly reduce reactive power dispatch limit violations.
Placement is a critical task with high computation complexity in VLSI physical design. Modern analytical placers formulate the placement objective as a nonlinear optimization task, which suffers a long iteration time....
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Reconfigurable holographic surfaces (RHSs) can generate the desired directional beam by controlling the radiation amplitude of reference wave, and thus is an effective alternative to conventional analogue beamforming ...
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