We use model predictive control (MPC) for the optimal energy distribution in non-residential buildings. Our approach is special in that it treats thermal and electrical energy flows simultaneously. Our sample applicat...
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We use model predictive control (MPC) for the optimal energy distribution in non-residential buildings. Our approach is special in that it treats thermal and electrical energy flows simultaneously. Our sample application is a real office building, where components such as heat pumps and heating rods introduce discrete variables. This implies the optimal control problem that must be solved for MPC is a mixed-integer quadratic programming (MIQP) problem. Because both continuous and integer variables are involved, the computation times may become prohibitive for use in real-time. We explore a computationally efficient approximation that replaces integer variables by continuous variables for later time steps along the horizon. The performance of MPC using this method is investigated in simulations and the results are compared to those for the original MIQP problem and solution. Our method significantly reduces computational time while achieving a nearly optimal solution.
One of the key aspects of the Physical Internet (PI) is the use of standardized, modular containers that enable the coordination of shipments across the supply chain. However, a key open question is how will limiting ...
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One of the key aspects of the Physical Internet (PI) is the use of standardized, modular containers that enable the coordination of shipments across the supply chain. However, a key open question is how will limiting the choice of containers impact the amount of volume that is shipped? We present a mathematical model to determine that impact and report our results for data sets that are based on data from a consumer packaged goods company.
Since the farm financial crisis of the 1980s, Farm Credit System banks continue to merge and consolidate to enhance competitiveness. Two mixed-integer programming models of AgChoice Agricultural Credit Association (AC...
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Since the farm financial crisis of the 1980s, Farm Credit System banks continue to merge and consolidate to enhance competitiveness. Two mixed-integer programming models of AgChoice Agricultural Credit Association (ACA), a recently merged ACA in Pennsylvania, were developed to determine the optimal number, location, and territory of branches. The approach suggests useful information can be determined regarding the reconfiguration process after bank mergers, especially given the fact that the current AgChoice ACA configuration is available for comparison purposes.
This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-...
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This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-term strategic uncertainty and short-term operational uncertainty in a single optimization model. The model supports wind farm owners in making strategic decisions regarding the number, placement, charter length, and types of vessels to charter, to meet maintenance demands throughout the lifetime of a wind farm. To evaluate the quality of strategic fleet size and mix decisions, the model also considers the operational decisions of how to utilize the fleet to support maintenance operations. The model accounts for strategic uncertainties that have not been considered in previously developed optimization models for offshore wind, such as uncertainty related to long-term trends in electricity prices and subsidy levels, the stepwise development of wind farms, and technology development in the vessel industry. To solve the proposed stochastic programming model we have developed an ad hoc integer L-shaped method, with customized optimality cuts. The computational experiments show that the proposed method outperforms solving the deterministic equivalent using a commercial MIP solver.
作者：
Mallach, SvenUniv Bonn
High Performance Comp & Analyt Lab Friedrich Hirzebruch Allee 8 D-53115 Bonn Germany
We present and compare novel binary programs for linear ordering problems that involve the notion of asymmetric betweenness and expose relations to the quadratic linear ordering problem and its linearization. While tw...
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We present and compare novel binary programs for linear ordering problems that involve the notion of asymmetric betweenness and expose relations to the quadratic linear ordering problem and its linearization. While two of the binary programs prove particularly superior from a computational point of view when many or all betweenness relations shall be modeled, the others arise as natural formulations that resemble important theoretical correspondences and provide a compact alternative for sparse problem instances. A reasoning for the strengths and weaknesses of the different formulations is derived by means of polyhedral considerations with respect to their continuous relaxations.& COPY;2023 The Author(s). Published by Elsevier Ltd on behalf of Association of European Operational Research Societies (EURO). This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).
Synthesis of sustainable processing pathway is an important initial step in deciding investments in carbon capture, utilization, and sequestration (CCUS). For a best decision, it is necessary to analyze a very large n...
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Synthesis of sustainable processing pathway is an important initial step in deciding investments in carbon capture, utilization, and sequestration (CCUS). For a best decision, it is necessary to analyze a very large number of potential processing pathways at once in terms of their economics and net carbon emission. Such analysis may also reveal which parts of a pathway incur significant portions of the costs and carbon emissions, suggesting hotspots for improvement. Frameworks used should also be flexible enough to accommodate varying feed conditions and market/emission data as they tend to vary according to the sources of CO 2 and geographical locations. The superstructure method along with a state-task network (STN) representation offers such flexibility in analyzing a CCUS system. This work proposes to use a STN representation of a process in a superstructure composed of feeds, processes, and products, to represent and optimize among various options of CCUS pathways through mathematical programming. A case study is conducted to illustrate the utility of the STN representation in the CCUS superstructure optimization.
Amsterdam, a growing city of over 800,000 people in the Netherlands, is struggling to collect waste. While residents in most districts of the city use underground bins to deposit their garbage, the historic Centrum di...
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Amsterdam, a growing city of over 800,000 people in the Netherlands, is struggling to collect waste. While residents in most districts of the city use underground bins to deposit their garbage, the historic Centrum district continues to rely on curbside collection. As such, the streets around the UNESCO-World-Heritage canals are lined with garbage bags as trash trucks rumble down roads centuries old and ill-fitted for vehicles of such size. This paper assesses the viability of moving Centrum trash collection to the canals with a fleet of tug boats and floating dumpsters. It does so by using a combination of GIS tools and integerprogramming to determine the quantity and optimal collection locations while ensuring that an average Centrum resident walks no farther than denizens of the other Amsterdam districts. Additionally, it proposes a schedule for emptying floating dumpsters based on one comparable to the current truck system. The results of this paper suggest that mobile trash collection using the canals is a viable solution that could reduce noise, pollution, and congestion, thus improving the quality of Amsterdam’s historic cityscape.
This paper deals with the problem of optimal control at an isolated oversaturated intersection equipped with a signa1-group-oriented controller. The problem we consider is to determine elements of the signal plan (sta...
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This paper deals with the problem of optimal control at an isolated oversaturated intersection equipped with a signa1-group-oriented controller. The problem we consider is to determine elements of the signal plan (stages, their duration and sequence) so as to maximize the number of vehicles that can pass through the intersection during one cycle. The concents of signal plan structure, admissible stage sequences, and structural constraints are introduced, and the optimization problem is stated as the problem of finding the best closed path through the graph of possible sequences. The optimization technique is of branch-and -bound type. The proposed method gives an exact procedure for simultaneous determination of all signal plan elements, except for the cycle time. An illustrative example is also included.
In this paper we present an application of the scenario aggregation approach proposed by Rockafellar and Wets to a simple standard multi-product multi-period production planning problem with uncertain demand and setup...
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In this paper we present an application of the scenario aggregation approach proposed by Rockafellar and Wets to a simple standard multi-product multi-period production planning problem with uncertain demand and setup cost modelled by logical zero-one variables. The uncertainty in demand is expressed by a number of demand scenarios. As compared with more traditional approaches that require distributional assumptions and/or estimates of parameters from historical demand data, the scenario approach offers greater flexibility and makes it possible to take subjective information into account. The scenario aggregation principle and the corresponding progressive hedging algorithm offer a theoretically sound basis for generating consistent solutions for production planning models with uncertain demand. Since the production planning problem studied in this paper is of mixed-integer type the original scenario aggregation approach cannot be applied directly. However, since the integer variables in the production planning model are indirectly coupled to the continuous production decisions an alternative method in which only the production quantities are used to couple the different realizations can be used. This paper is a first attempt to perform this form of coupling. We illustrate the ideas on a small example and use this example to demonstrate how the solution can be evaluated in terms of flexibility measures.
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