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Academic literature on the topic 'Dynamic Constrained Problems'

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Published: 10 December 2022
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Journal articles on the topic "Dynamic Constrained Problems"

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Wang, Qiuzhen, Zhibing Liang, Juan Zou, Xiangdong Yin, Yuan Liu, Yaru Hu, and Yizhang Xia. "Dynamic Constrained Boundary Method for Constrained Multi-Objective Optimization." Mathematics 10, no. 23 (November 26, 2022): 4459. http://dx.doi.org/10.3390/math10234459.

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When solving complex constrained problems, how to efficiently utilize promising infeasible solutions is an essential issue because these promising infeasible solutions can significantly improve the diversity of algorithms. However, most existing constrained multi-objective evolutionary algorithms (CMOEAs) do not fully exploit these promising infeasible solutions. In order to solve this problem, a constrained multi-objective optimization evolutionary algorithm based on the dynamic constraint boundary method is proposed (CDCBM). The proposed algorithm continuously searches for promising infeasible solutions between UPF (the unconstrained Pareto front) and CPF (the constrained Pareto front) during the evolution process by the dynamically changing auxiliary population of the constraint boundary, which continuously provides supplementary evolutionary directions to the main population and improves the convergence and diversity of the main population. Extensive experiments on three well-known test suites and three real-world constrained multi-objective optimization problems demonstrate that CDCBM is more competitive than seven state-of-the-art CMOEAs.
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Raha, Soumyendu, and Linda R. Petzold. "Constraint partitioning for structure in path-constrained dynamic optimization problems." Applied Numerical Mathematics 39, no. 1 (October 2001): 105–26. http://dx.doi.org/10.1016/s0168-9274(01)00055-1.

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Raha, Soumyendu, and Linda R. Petzold. "Constraint Partitioning for Stability in Path-Constrained Dynamic Optimization Problems." SIAM Journal on Scientific Computing 22, no. 6 (January 2001): 2051–74. http://dx.doi.org/10.1137/s1064827500372390.

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Frank, Jeremy. "Revisiting dynamic constraint satisfaction for model-based planning." Knowledge Engineering Review 31, no. 5 (November 2016): 429–39. http://dx.doi.org/10.1017/s0269888916000242.

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AbstractAs planning problems become more complex, it is increasingly useful to integrate complex constraints on time and resources into planning models, and use constraint reasoning approaches to help solve the resulting problems. Dynamic constraint satisfaction is a key enabler of automated planning in the presence of such constraints. In this paper, we identify some limitations with the previously developed theories of dynamic constraint satisfaction. We identify a minimum set of elementary transformations from which all other transformations can be constructed. We propose a new classification of dynamic constraint satisfaction transformations based on a formal criteria, namely the change in the fraction of solutions. This criteria can be used to evaluate elementary transformations of a constraint satisfaction problem as well as sequences of transformations. We extend the notion of transformations to include constrained optimization problems. We discuss how this new framework can inform the evolution of planning models, automated planning algorithms, and mixed-initiative planning.
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Wang, J. T. "Inverse Dynamics of Constrained Multibody Systems." Journal of Applied Mechanics 57, no. 3 (September 1, 1990): 750–57. http://dx.doi.org/10.1115/1.2897087.

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A method for analyzing constrained multibody systems is presented. The method is applicable to a class of problems in which the multibody system is subjected to both force and kinematic constraints. This class of problems cannot be solved by using the classical methods. The method is based upon the concept of partial velocity and generalized forces of Kane’s method to permit the choice of constraint forces for fulfilling both kinematic and force constraints. Thus, the constraint forces or moments at convenient points or bodies may be specified in any desired form. For many applications, the method also allows analysts to choose a constant coefficient matrix for the undetermined force term to greatly reduce the burden of repeatedly computing its orthogonal complement matrix in solving the differential algebraic dynamic equations. Two examples illustrating the concepts are presented.
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Rustichini, Aldo. "Dynamic Programming Solution of Incentive Constrained Problems." Journal of Economic Theory 78, no. 2 (February 1998): 329–54. http://dx.doi.org/10.1006/jeth.1997.2371.

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Li, Xi, Sanyou Zeng, Changhe Li, and Jiantao Ma. "Many-objective optimization with dynamic constraint handling for constrained optimization problems." Soft Computing 21, no. 24 (July 27, 2016): 7435–45. http://dx.doi.org/10.1007/s00500-016-2286-8.

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Fu, Jingli, Lijun Zhang, Shan Cao, Chun Xiang, and Weijia Zao. "A Symplectic Algorithm for Constrained Hamiltonian Systems." Axioms 11, no. 5 (May 7, 2022): 217. http://dx.doi.org/10.3390/axioms11050217.

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In this paper, a symplectic algorithm is utilized to investigate constrained Hamiltonian systems. However, the symplectic method cannot be applied directly to the constrained Hamiltonian equations due to the non-canonicity. We firstly discuss the canonicalization method of the constrained Hamiltonian systems. The symplectic method is used to constrain Hamiltonian systems on the basis of the canonicalization, and then the numerical simulation of the system is carried out. An example is presented to illustrate the application of the results. By using the symplectic method of constrained Hamiltonian systems, one can solve the singular dynamic problems of nonconservative constrained mechanical systems, nonholonomic constrained mechanical systems as well as physical problems in quantum dynamics, and also available in many electromechanical coupled systems.
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Cheng, Dong Mei, Jian Huang, Hong Jiang Li, and Jing Sun. "Dynamic Sub-Population Genetic Algorithm Combined with Dynamic Penalty Function to Solve Constrained Optimization Problems." Key Engineering Materials 450 (November 2010): 560–63. http://dx.doi.org/10.4028/www.scientific.net/kem.450.560.

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This paper presents a new method of dynamic sub-population genetic algorithm combined with modified dynamic penalty function to solve constrained optimization problems. The new method ensures the final optimal solution yields all constraints through re-organizing all individuals of each generation into two sub-populations according to the feasibility of individuals. And the modified dynamic penalty function gradually increases the punishment to bad individuals with the development of the evolution. With the help of the penalty function and other improvements, the new algorithm prevents local convergence and iteration wandering fluctuations. Typical instances are used to evaluate the optimizing performance of this new method; and the result shows that it can deal with constrained optimization problems well.
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Dadebo, S. A., and K. B. Mcauley. "Dynamic optimization of constrained chemical engineering problems using dynamic programming." Computers & Chemical Engineering 19, no. 5 (May 1995): 513–25. http://dx.doi.org/10.1016/0098-1354(94)00086-4.

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Dissertations / Theses on the topic "Dynamic Constrained Problems"

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Wang, Alexander C. (Alexander Che-Wei). "Approximate value iteration approaches to constrained dynamic portfolio problems." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30089.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 173-176).
This thesis considers a discrete-time, finite-horizon dynamic portfolio problem where an investor makes sequential investment decisions with the goal of maximizing expected terminal wealth. We allow non-standard utility functions and constraints upon the portfolio selections at each time. These problem formulations may be computationally difficult to address through traditional optimal control techniques due to the high dimensionality of the state space and control space. We consider suboptimal solution methods based on approximate value iteration. The primary innovation is the use of mean-variance portfolio selection methods. We present two case studies that employ these approximate value iteration methods. The first case study explores the effect of an insolvency constraint that prohibits further investing when an investor reaches non-positive wealth. When the investor has an exponential utility function, the insolvency constraint leads to more conservative investment policies when there are many investment periods remaining, except when wealth is very low. The second case study explores the effects of dollar position constraints that represent limited liquidity in certain investment strategies. When the investor has a CRRA utility function, we find that these constraints lead to non-myopic policies that are more conservative than the constrained myopic policy.
by Alexander C. Wang.
Ph.D.
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Loxton, Ryan Christopher. "Optimal control problems involving constrained, switched, and delay systems." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/1479.

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In this thesis, we develop numerical methods for solving five nonstandard optimal control problems. The main idea of each method is to reformulate the optimal control problem as, or approximate it by, a nonlinear programming problem. The decision variables in this nonlinear programming problem influence its cost function (and constraints, if it has any) implicitly through the dynamic system. Hence, deriving the gradient of the cost and the constraint functions is a difficult task. A major focus of this thesis is on developing methods for computing these gradients. These methods can then be used in conjunction with a gradient-based optimization technique to solve the optimal control problem efficiently.The first optimal control problem that we consider has nonlinear inequality constraints that depend on the state at two or more discrete time points. These time points are decision variables that, together with a control function, should be chosen in an optimal manner. To tackle this problem, we first approximate the control by a piecewise constant function whose values and switching times (the times at which it changes value) are decision variables. We then apply a novel time-scaling transformation that maps the switching times to fixed points in a new time horizon. This yields an approximate dynamic optimization problem with a finite number of decision variables. We develop a new algorithm, which involves integrating an auxiliary dynamic system forward in time, for computing the gradient of the cost and constraints in this approximate problem.The second optimal control problem that we consider has nonlinear continuous inequality constraints. These constraints restrict both the state and the control at every point in the time horizon. As with the first problem, we approximate the control by a piecewise constant function and then transform the time variable. This yields an approximate semi-infinite programming problem, which can be solved using a penalty function algorithm. A solution of this problem immediately furnishes a suboptimal control for the original optimal control problem. By repeatedly increasing the number of parameters used in the approximation, we can generate a sequence of suboptimal controls. Our main result shows that the cost of these suboptimal controls converges to the minimum cost.The third optimal control problem that we consider is an applied problem from electrical engineering. Its aim is to determine an optimal operating scheme for a switchedcapacitor DC-DC power converter—an electronic device that transforms one DC voltage into another by periodically switching between several circuit topologies. Specifically, the optimal control problem is to choose the times at which the topology switches occur so that the output voltage ripple is minimized and the load regulation is maximized. This problem is governed by a switched system with linear subsystems (each subsystem models one of the power converter’s topologies). Moreover, its cost function is non-smooth. By introducing an auxiliary dynamic system and transforming the time variable (so that the topology switching times become fixed), we derive an equivalent semi-infinite programming problem. This semi-infinite programming problem, like the one that approximates the continuously-constrained optimal control problem, can be solved using a penalty function algorithm.The fourth optimal control problem that we consider involves a general switched system, which includes the model of a switched-capacitor DC-DC power converter as a special case. This switched system evolves by switching between several subsystems of nonlinear ordinary differential equations. Furthermore, each subsystem switch is accompanied by an instantaneous change in the state. These instantaneous changes—so-called state jumps—are influenced by control variables that, together with the subsystem switching times, should be selected in an optimal manner. As with the previous optimal control problems, we tackle this problem by transforming the time variable to obtain an equivalent problem in which the switching times are fixed. However, the functions governing the state jumps in this new problem are discontinuous. To overcome this difficulty, we introduce an approximate problem whose state jumps are governed by smooth functions. This approximate problem can be solved using a nonlinear programming algorithm. We prove an important convergence result that links the approximate problem’s solution with the original problem’s solution.The final optimal control problem that we consider is a parameter identification problem. The aim of this problem is to use given experimental data to identify unknown state-delays in a nonlinear delay-differential system. More precisely, the optimal control problem involves choosing the state-delays to minimize a cost function measuring the discrepancy between predicted and observed system output. We show that the gradient of this cost function can be computed by solving an auxiliary delay-differential system. On the basis of this result, the optimal control problem can be formulated—and hence solved—as a standard nonlinear programming problem.
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Kangwalklai, Sasikul. "Time Dynamic Label-Constrained Shortest Path Problems with Application to TRANSIMS: A Transportation Planning System." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/31037.

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TRANSIMS (Transportation Analysis Simulation System) is part of a multi-track Travel Model Improvement Program sponsored by the U. S. Department of Transportation (DOT), and the Environmental Protection Agency (EPA). The main objective of this thesis is to enhance and implement a principal module in TRANSIMS, called the Route Planner Module. The purpose of the Route Planner Module is to find time-dependent label-constrained shortest paths for transportation activities performed by travelers in the system. There are several variations of shortest path problems and algorithms that vary by application, contexts, complexity, required data, and computer implementation techniques. In general, these variants require some combination of the following inputs: a network consisting of nodes and links, and a travel time function on each link, which could be a time-independent or a time-dependent function, where the time-dependent functions account for time-of-day delays resulting from actual travel conditions such as peak-hour congestion. The problem then seeks a shortest path between one or more origin-destination pairs. A new variant, introduced in the context of TRANSIMS and which is the focus of the present study, also specifies labels for each arc denoting particular modes of travel, along with strings of admissible labels that delineate the permissible travel mode sequences that could be adopted by the user in traveling from the origin to the destination of the trip. The technique adopted by TRANSIMS to identify a suitable travel route for any user is a variant of Dijkstra's procedure for finding shortest paths, which is suitably modified to accommodate time-dependent travel times and label sequence constraints. The underlying problem is referred to as a Time-Dependent Label-Constrained Shortest Path Problem. The main objective of this research is to improve upon this procedure and study its implementation in order to develop a more effective scheme for determining time-dependent label-constrained shortest paths as a practical routing tool in multimodal transportation networks. Specifically, we enhance the following features of this procedure: (a) We recommend a method to work implicitly with a certain composition graph G* that combines the transportation network with the admissible label-sequence graph. This graph G* captures all possible paths for a given single trip starting from the origin node and ending at the destination node, while conforming with the admissible mode string. (b) We use more modern partitioned shortest path algorithmic schemes to implement the time-dependent label-constrained procedure. (c) We introduce the notion of curtailing search based on various indicators of progress and projected travel times to complete the trip. Finally, computer programs in C++ are written to implement the proposed overall algorithm, and are applied to solve some real multimodal transportation network problems. The indicators used to evaluate the performance of the algorithm include (i) time taken for computation on the real network, (ii) quality of solution obtained, (iii) ease of implementation, and (iv) extensibility of the algorithm for solving other variants of the shortest path problem. The results exhibit that the proposed algorithm, even without the approximate curtailing of the search process, exhibits good performance in finding optimal routes for real multimodal transportation networks. Although the various heuristic curtailments result in only approximate solutions, typically, they run much faster than the exact algorithm for the intuitive reason that the shortest path tree developed grows more pointedly in the direction of the destination. Among the different strategies implemented, our results suggest that the scheme based on the geometric structure of the underlying network, using either a constant predictive term, or multiplying this term with a suitable exponential decay function, yields an attractive candidate for heuristically curtailing the search.
Master of Science
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Lokhov, Andrey Y. "Dynamic cavity method and problems on graphs." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112331/document.

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Un grand nombre des problèmes d'optimisation, ainsi que des problèmes inverses, combinatoires ou hors équilibre qui apparaissent en physique statistique des systèmes complexes, peuvent être représentés comme un ensemble des variables en interaction sur un certain réseau. Bien que la recette universelle pour traiter ces problèmes n'existe pas, la compréhension qualitative et quantitative des problèmes complexes sur des graphes a fait des grands progrès au cours de ces dernières années. Un rôle particulier a été joué par des concepts empruntés de la physique des verres de spin et la théorie des champs, qui ont eu beaucoup de succès en ce qui concerne la description des propriétés statistiques des systèmes complexes et le développement d'algorithmes efficaces pour des problèmes concrets.En première partie de cette thèse, nous étudions des problèmes de diffusion sur des réseaux, avec la dynamique hors équilibre. En utilisant la méthode de cavité sur des trajectoires dans le temps, nous montrons comment dériver des équations dynamiques dites "message-passing'' pour une large classe de modèles avec une dynamique unidirectionnelle -- la propriété clef qui permet de résoudre le problème. Ces équations sont asymptotiquement exactes pour des graphes localement en arbre et en général représentent une bonne approximation pour des réseaux réels. Nous illustrons cette approche avec une application des équations dynamiques pour résoudre le problème inverse d'inférence de la source d'épidémie dans le modèle "susceptible-infected-recovered''.Dans la seconde partie du manuscrit, nous considérons un problème d'optimisation d'appariement planaire optimal sur une ligne. En exploitant des techniques de la théorie de champs et des arguments combinatoires, nous caractérisons une transition de phase topologique qui se produit dans un modèle désordonné simple, le modèle de Bernoulli. Visant une application à la physique des structures secondaires de l'ARN, nous discutons la relation entre la transition d'appariement parfait-imparfait et la transition de basse température connue entre les états fondu et vitreux de biopolymère; nous proposons également des modèles généralisés qui suggèrent une correspondance exacte entre la matrice des contacts et la séquence des nucléotides, permettant ainsi de donner un sens à la notion des alphabets effectifs non-entiers
A large number of optimization, inverse, combinatorial and out-of-equilibrium problems, arising in the statistical physics of complex systems, allow for a convenient representation in terms of disordered interacting variables defined on a certain network. Although a universal recipe for dealing with these problems does not exist, the recent years have seen a serious progress in understanding and quantifying an important number of hard problems on graphs. A particular role has been played by the concepts borrowed from the physics of spin glasses and field theory, that appeared to be extremely successful in the description of the statistical properties of complex systems and in the development of efficient algorithms for concrete problems.In the first part of the thesis, we study the out-of-equilibrium spreading problems on networks. Using dynamic cavity method on time trajectories, we show how to derive dynamic message-passing equations for a large class of models with unidirectional dynamics -- the key property that makes the problem solvable. These equations are asymptotically exact for locally tree-like graphs and generally provide a good approximation for real-world networks. We illustrate the approach by applying the dynamic message-passing equations for susceptible-infected-recovered model to the inverse problem of inference of epidemic origin. In the second part of the manuscript, we address the optimization problem of finding optimal planar matching configurations on a line. Making use of field-theory techniques and combinatorial arguments, we characterize a topological phase transition that occurs in the simple Bernoulli model of disordered matching. As an application to the physics of the RNA secondary structures, we discuss the relation of the perfect-imperfect matching transition to the known molten-glass transition at low temperatures, and suggest generalized models that incorporate a one-to-one correspondence between the contact matrix and the nucleotide sequence, thus giving sense to the notion of effective non-integer alphabets
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Van, Der Linden A. S. Janet. "Dynamic meta-constraints : an approach to dealing with non-standard constraint satisfaction problems." Thesis, Oxford Brookes University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322242.

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Climent, Aunés Laura Isabel. "Robustness and stability in dynamic constraint satisfaction problems." Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/34785.

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Constraint programming is a paradigm wherein relations between variables are stated in the form of constraints. It is well-known that many real life problems can be modeled as Constraint Satisfaction Problems (CSPs). Much effort has been spent to increase the efficiency of algorithms for solving CSPs. However, many of these techniques assume that the set of variables, domains and constraints involved in the CSP are known and fixed when the problem is modeled. This is a strong limitation because many problems come from uncertain and dynamic environments, where both the original problem may evolve because of the environment, the user or other agents. In such situations, a solution that holds for the original problem can become invalid after changes. There are two main approaches for dealing with these situations: reactive and proactive approaches. Using reactive approaches entails re-solving the CSP after each solution loss, which is a time consuming. That is a clear disadvantage, especially when we deal with short-term changes, where solution loss is frequent. In addition, in many applications, such as on-line planning and scheduling, the delivery time of a new solution may be too long for actions to be taken on time, so a solution loss can produce several negative effects in the modeled problem. For a task assignment production system with several machines, it could cause the shutdown of the production system, the breakage of machines, the loss of the material/object in production, etc. In a transport timetabling problem, the solution loss, due to some disruption at a point, may produce a delay that propagates through the entire schedule. In addition, all the negative effects stated above will probably entail an economic loss. In this thesis we develop several proactive approaches. Proactive approaches use knowledge about possible future changes in order to avoid or minimize their effects. These approaches are applied before the changes occur. Thus, our approaches search for robust solutions, which have a high probability to remain valid after changes. Furthermore, some of our approaches also consider that the solutions can be easily adapted when they did not resist the changes in the original problem. Thus, these approaches search for stable solutions, which have an alternative solution that is similar to the previous one and therefore can be used in case of a value breakage. In this context, sometimes there exists knowledge about the uncertain and dynamic environment. However in many cases, this information is unknown or hard to obtain. For this reason, for the majority of our approaches (specifically 3 of the 4 developed approaches), the only assumptions made about changes are those inherent in the structure of problems with ordered domains. Given this framework and therefore the existence of a significant order over domain values, it is reasonable to assume that the original bounds of the solution space may undergo restrictive or relaxed modifications. Note that the possibility of solution loss only exists when changes over the original bounds of the solution space are restrictive. Therefore, the main objective for searching robust solutions in this framework is to find solutions located as far away as possible from the bounds of the solution space. In order to meet this criterion, we propose several approaches that can be divided in enumeration-based techniques and a search algorithm.
Climent Aunés, LI. (2013). Robustness and stability in dynamic constraint satisfaction problems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34785
TESIS
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Vassiliadis, Vassilios. "Computational solution of dynamic optimization problems with general differential-algebraic constraints." Thesis, Imperial College London, 1993. http://hdl.handle.net/10044/1/7567.

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Voccia, Stacy Ann. "Stochastic last-mile delivery problems with time constraints." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/1924.

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When a package is shipped, the customer often requires the delivery to be made within a particular time window or by a deadline. However, meeting such time requirements is difficult, and delivery companies may not always know ahead of time which customers will need a delivery. In this thesis, we present models and solution approaches for two stochastic last-mile delivery problems in which customers have delivery time constraints and customer presence is known in advance only according to a probability distribution. Our solutions can help reduce the operational costs of delivery while improving customer service. The first problem is the probabilistic traveling salesman problem with time windows (PTSPTW). In the PTSPTW, customers have both a time window and a probability of needing a delivery on any given day. The objective is to find a pre-planned route with an expected minimum cost. We present computational results that characterize the PTSPTW solutions. We provide insights for practitioners on when solving the PTSPTW is beneficial compared to solving the deterministic analogue of the problem. The second problem is the same-day delivery problem (SDDP). The SDDP is a dynamic and stochastic pick-up and delivery problem. In the SDDP, customers make delivery requests throughout the day and vehicles are dispatched from a warehouse or brick and mortar store to serve the requests. Associated with each request is a request deadline or time window. In order to make better-informed decisions, our solution approach incorporates information about future requests into routing decisions by using a sample scenario planning approach with a consensus function. We also introduce an analytical result that identifies when it is beneficial for vehicles to wait at the depot. We present a wide range of computational experiments that demonstrate the value of our approaches.
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Mai, Dung Hoang. "A Heuristic for the Constrained One-Sided Two-Layered Crossing Reduction Problem for Dynamic Graph Layout." NSUWorks, 2011. http://nsuworks.nova.edu/gscis_etd/225.

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Data in real-world graph drawing applications often change frequently but incrementally. Any drastic change in the graph layout could disrupt a user's "mental map." Furthermore, real-world applications like enterprise process or e-commerce graphing, where data change rapidly in both content and quantity, demand a comprehensive responsiveness when rendering the graph layout in a multi-user environment in real time. Most standard static graph drawing algorithms apply global changes and redraw the entire graph layout whenever the data change. The new layout may be very different from the previous layout and the time taken to redraw the entire graph degrades quickly as the amount of graph data grows. Dynamic behavior and the quantity of data generated by real-world applications pose challenges for existing graph drawing algorithms in terms of incremental stability and scalability. A constrained hierarchical graph drawing framework and modified Sugiyama heuristic were developed in this research. The goal of this research was to improve the scalability of the constrained graph drawing framework while preserving layout stability. The framework's use of the relational data model shifts the graph application from the traditional desktop to a collaborative and distributed environment by reusing vertex and edge information stored in a relational database. This research was based on the work of North and Woodhull (2001) and the constrained crossing reduction problem proposed by Forster (2004). The result of the constrained hierarchical graph drawing framework and the new Sugiyama heuristic, especially the modified barycenter algorithms, were tested and evaluated against the Graphviz framework and North and Woodhull's (2001) online graph drawing framework. The performance test results showed that the constrained graph drawing framework run time is comparable with the performance of the Graphviz framework in terms of generating static graph layouts, which is independent of database accesses. Decoupling graph visualization from the graph editing modules improved scalability, enabling the rendering of large graphs in real time. The visualization test also showed that the constrained framework satisfied the aesthetic criteria for constrained graph layouts. Future enhancements for this proposed framework include implementation of (1) the horizontal coordinate assignment algorithm, (2) drawing polylines for multilayer edges in the rendering module, and (3) displaying subgraphs for very large graph layouts.
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Zhu, Xiaoyan. "The dynamic, resource-constrained shortest path problem on an acyclic graph with application in column generation and literature review on sequence-dependent scheduling." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4996.

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This dissertation discusses two independent topics: a resource-constrained shortest-path problem (RCSP) and a literature review on scheduling problems involving sequence-dependent setup (SDS) times (costs). RCSP is often used as a subproblem in column generation because it can be used to solve many practical problems. This dissertation studies RCSP with multiple resource constraints on an acyclic graph, because many applications involve this configuration, especially in column genetation formulations. In particular, this research focuses on a dynamic RCSP since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-time “preliminary” phase to transform RCSP into an unconstrained shortest path problem (SPP) and then solves the resulting SPP after new values of dual variables are used to update objective function coefficients (i.e., reduced costs) at each iteration. Network reduction techniques are considered to remove some nodes and/or arcs permanently in the preliminary phase. Specified techniques are explored to reoptimize when only several coefficients change and for dealing with forbidden and prescribed arcs in the context of a column generation/branch-and-bound approach. As a benchmark method, a label-setting algorithm is also proposed. Computational tests are designed to show the effectiveness of the proposed algorithms and procedures. This dissertation also gives a literature review related to the class of scheduling problems that involve SDS times (costs), an important consideration in many practical applications. It focuses on papers published within the last decade, addressing a variety of machine configurations - single machine, parallel machine, flow shop, and job shop - reviewing both optimizing and heuristic solution methods in each category. Since lot-sizing is so intimately related to scheduling, this dissertation reviews work that integrates these issues in relationship to each configuration. This dissertation provides a perspective of this line of research, gives conclusions, and discusses fertile research opportunities posed by this class of scheduling problems. since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-time
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Books on the topic "Dynamic Constrained Problems"

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A. S. Janet van der Linden. Dynamic meta-constraints: An approach to dealing with non-standard constraint satisfaction problems. Oxford: Oxford Brookes University, 2000.

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Claude, Le Pape, and Nuijten Wim, eds. Constraint-based scheduling: Applying constraint programming to scheduling problems. Boston: Kluwer Academic, 2001.

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First-passage problems: A probabilistic dynamic analysis for degraded structures. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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First-passage problems: A probabilistic dynamic analysis for degraded structures. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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C, Chamis C., and United States. National Aeronautics and Space Administration., eds. First-passage problems: A probabilistic dynamic analysis for degraded structures. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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Boudreau, Joseph F., and Eric S. Swanson. Many body dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0018.

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Specialized techniques for solving the classical many-body problem are explored in the context of simple gases, more complicated gases, and gravitating systems. The chapter starts with a brief review of some important concepts from statistical mechanics and then introduces the classic Verlet method for obtaining the dynamics of many simple particles. The practical problems of setting the system temperature and measuring observables are discussed. The issues associated with simulating systems of complex objects form the next topic. One approach is to implement constrained dynamics, which can be done elegantly with iterative methods. Gravitational systems are introduced next with stress on techniques that are applicable to systems of different scales and to problems with long range forces. A description of the recursive Barnes-Hut algorithm and particle-mesh methods that speed up force calculations close out the chapter.
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Md. Ali, Azham. The political economy of external auditing in Malaysia 1957 - 1997. UUM Press, 1999. http://dx.doi.org/10.32890/9839559656.

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This work investigates the role and contribution of external auditing as practiced in Malaysian society in the first 40 years since independence in 1957.It applies the political economic approach, which emphasises the social relations aspects of professional activity rather than economic forces alone.The political economic approach is applied by utilising an enlarged exogenous framework of processual change analysis.This particular interpretive framework views external auditing in Malaysia over the forty year period (1957-1997) as an open, dynamic social system comprising two pattern transformations.The study focuses specifically on the historical development of, and environment influences on the countrys audit practice and provides insights into the operational form of contemporary audit practice and the historical, social, economic and political determinants of that form.The writer extrapolates that in all probability, the future of auditing in Malaysia will continue to be constrained by unresolved problems; audit in Malaysia seems to be case of the triumph of hope over experience.
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Baptiste, Philippe, Claude Le Pape, and Wim Nuijten. Constraint-Based Scheduling - Applying Constraint Programming to Scheduling Problems (International Series in Operations Research and Management Science, ... in Operations Research & Management Science). Springer, 2001.

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Silberstein, Michael, W. M. Stuckey, and Timothy McDevitt. Resolving Puzzles, Problems, and Paradoxes from General Relativity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198807087.003.0004.

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The main thread of chapter 3 introduces general relativity (GR), Big Bang cosmology, and closed timelike curves, showing how the ant’s-eye view leads to the puzzle of the creation of the universe, the horizon problem, the flatness problem, the low entropy problem, and the paradoxes of closed time-like curves. All these puzzles, problems, and paradoxes of the dynamical universe are resolved using the God’s-eye view of the adynamical block universe. Accordingly, Einstein’s equations of GR are not understood dynamically, but rather adynamically, that is, as a global self-consistency constraint between the spacetime metric and stress–energy tensor throughout the spacetime manifold. This is “spatiotemporal ontological contextuality” as applied to GR. The philosophical nuances such as the status of the block universe argument in GR and debates about the Past Hypothesis have been placed in Philosophy of Physics for Chapter 3. The associated formalism and computations are in Foundational Physics for Chapter 3.
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Silberstein, Michael, W. M. Stuckey, and Timothy McDevitt. Relational Blockworld and Quantum Mechanics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198807087.003.0005.

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The main thread of chapter 4 introduces some of the major mysteries and interpretational issues of quantum mechanics (QM). These mysteries and issues include: quantum superposition, quantum nonlocality, Bell’s inequality, entanglement, delayed choice, the measurement problem, and the lack of counterfactual definiteness. All these mysteries and interpretational issues of QM result from dynamical explanation in the mechanical universe and are dispatched using the authors’ adynamical explanation in the block universe, called Relational Blockworld (RBW). A possible link between RBW and quantum information theory is provided. The metaphysical underpinnings of RBW, such as contextual emergence, spatiotemporal ontological contextuality, and adynamical global constraints, are provided in Philosophy of Physics for Chapter 4. That is also where RBW is situated with respect to retrocausal accounts and it is shown that RBW is a realist, psi-epistemic account of QM. All the relevant formalism for this chapter is provided in Foundational Physics for Chapter 4.
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Book chapters on the topic "Dynamic Constrained Problems"

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Thornton, John, and Abdul Sattar. "Dynamic constraint weighting for over-constrained problems." In PRICAI’98: Topics in Artificial Intelligence, 377–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0095285.

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Richter, Hendrik. "Memory Design for Constrained Dynamic Optimization Problems." In Applications of Evolutionary Computation, 552–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12239-2_57.

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Aragón, Victoria S., Susana C. Esquivel, and Carlos A. Coello. "Artificial Immune System for Solving Dynamic Constrained Optimization Problems." In Metaheuristics for Dynamic Optimization, 225–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30665-5_11.

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Filipiak, Patryk, and Piotr Lipinski. "Making IDEA-ARIMA Efficient in Dynamic Constrained Optimization Problems." In Applications of Evolutionary Computation, 882–93. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16549-3_71.

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Ruxton, David J. W. "Differential Dynamic Programming and State Variable Inequality Constrained Problems." In Mechanics and Control, 223–34. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2425-0_19.

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Richter, Hendrik, and Franz Dietel. "Solving Dynamic Constrained Optimization Problems with Asynchronous Change Pattern." In Applications of Evolutionary Computation, 334–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20525-5_34.

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Nguyen, Trung Thanh, and Xin Yao. "Evolutionary Optimization on Continuous Dynamic Constrained Problems - An Analysis." In Studies in Computational Intelligence, 193–217. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38416-5_8.

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Li, Xi, Sanyou Zeng, Liting Zhang, and Guilin Zhang. "Combining Dynamic Constrained Many-Objective Optimization with DE to Solve Constrained Optimization Problems." In Communications in Computer and Information Science, 64–73. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0356-1_7.

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Filipiak, Patryk, Krzysztof Michalak, and Piotr Lipinski. "A Predictive Evolutionary Algorithm for Dynamic Constrained Inverse Kinematics Problems." In Lecture Notes in Computer Science, 610–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28942-2_55.

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Kuenne, Robert E. "Exact and Approximate Solution of Constrained Dynamic Combinatorial Problems in Space." In General Equilibrium Economics, 278–305. London: Palgrave Macmillan UK, 1992. http://dx.doi.org/10.1007/978-1-349-12752-8_13.

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Conference papers on the topic "Dynamic Constrained Problems"

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Nguyen, Trung Thanh, and Xin Yao. "Benchmarking and solving dynamic constrained problems." In 2009 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2009. http://dx.doi.org/10.1109/cec.2009.4983012.

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Przybylski, Bartłomiej. "Precedence constrained position-dependent scheduling on parallel machines via schedule transformations." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p67-69.

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Bankes. "Constrained differential optimization for temporally dynamic problems." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118304.

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Hamza, Noha, Saber Elsayed, Ruhul Sarker, and Daryl Essam. "Solving constrained problems with dynamic objective functions." In 2022 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2022. http://dx.doi.org/10.1109/cec55065.2022.9870354.

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Shi, Jian, Peter B. Luh, Shi-Chung Chang, and Tsu-Shuan Chang. "A Method for Constrained Dynamic Optimization Problems." In 1990 American Control Conference. IEEE, 1990. http://dx.doi.org/10.23919/acc.1990.4790847.

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Kurc, Wiesław, and Stanisław Gawiejnowicz. "Directed sets, Möbius inversing formula and time-dependent scheduling on precedence-constrained machines." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p51-54.

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Ameca-Alducin, Maria-Yaneli, Maryam Hasani-Shoreh, Wilson Blaikie, Frank Neumann, and Efren Mezura-Montes. "A Comparison of Constraint Handling Techniques for Dynamic Constrained Optimization Problems." In 2018 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2018. http://dx.doi.org/10.1109/cec.2018.8477750.

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Przybylski, Bartłomiej. "Precedence constrained parallel-machine scheduling of position-dependent unit jobs." In The Second International Workshop on Dynamic Scheduling Problems. Polish Mathematical Society, 2018. http://dx.doi.org/10.14708/isbn.978-83-951298-0-3p77-80.

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Soltani-Zarrin, Rana, Amin Zeiaee, and Suhada Jayasuriya. "Pointwise Angle Minimization: A Method for Guiding Wheeled Robots Based on Constrained Directions." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6279.

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In this paper we consider the point-to-point steering of a two wheeled differential drive mobile robot subject to constrained control inputs where the robot is expected to follow a given path between initial and final points. Formulation of this steering task as a constrained optimal control problem leads to nonlinear two-point boundary value problems. To avoid dealing with boundary value problems while alleviating the complications in analysis of systems with holonomic/non-holonomic constraints, we tackle the problem from a different perspective. This paper proposes a general framework for guiding wheeled robots using constrained direction method. The proposed scheme is equipped with pointwise angle minimization, a search algorithm useful in devising control strategies for steering problems. In addition to computational efficiency, one of the main advantages of the proposed scheme is that it does not impose any restrictive assumptions on the robot’s model. In this paper, kinematics of the robot under the assumption of rolling without slipping has been used as the model of the system and the efficiency of the proposed navigation scheme is illustrated through simulation results. However, the proposed scheme can be applied to more complicated models representing the two wheeled differential robots such as dynamics under slip occurrence.
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Potter, T. E., K. D. Willmert, and M. Sathyamoorthy. "Nonlinear Optimal Design of Dynamic Mechanical Systems." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0350.

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Abstract Mechanism path generation problems which use link deformations to improve the design lead to optimization problems involving a nonlinear sum-of-squares objective function subjected to a set of linear and nonlinear constraints. Inclusion of the deformation analysis causes the objective function evaluation to be computationally expensive. An optimization method is presented which requires relatively few objective function evaluations. The algorithm, based on the Gauss method for unconstrained problems, is developed as an extension of the Gauss constrained technique for linear constraints and revises the Gauss nonlinearly constrained method for quadratic constraints. The derivation of the algorithm, using a Lagrange multiplier approach, is based on the Kuhn-Tucker conditions so that when the iteration process terminates, these conditions are automatically satisfied. Although the technique was developed for mechanism problems, it is applicable to any optimization problem having the form of a sum of squares objective function subjected to nonlinear constraints.
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Reports on the topic "Dynamic Constrained Problems"

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Kholoshyn, Ihor V., Olga V. Bondarenko, Olena V. Hanchuk, and Iryna M. Varfolomyeyeva. Cloud technologies as a tool of creating Earth Remote Sensing educational resources. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3885.

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This article is dedicated to the Earth Remote Sensing (ERS), which the authors believe is a great way to teach geography and allows forming an idea of the actual geographic features and phenomena. One of the major problems that now constrains the active introduction of remote sensing data in the educational process is the low availability of training aerospace pictures, which meet didactic requirements. The article analyzes the main sources of ERS as a basis for educational resources formation with aerospace images: paper, various individual sources (personal stations receiving satellite information, drones, balloons, kites and balls) and Internet sources (mainstream sites, sites of scientific-technical organizations and distributors, interactive Internet geoservices, cloud platforms of geospatial analysis). The authors point out that their geospatial analysis platforms (Google Earth Engine, Land Viewer, EOS Platform, etc.), due to their unique features, are the basis for the creation of information thematic databases of ERS. The article presents an example of such a database, covering more than 800 aerospace images and dynamic models, which are combined according to such didactic principles as high information load and clarity.
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An Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0741.

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Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form. The output non-linearities can be approximated using a quadratic model, which creates a problem in the linear-quadratic framework. This facilitates the direct application of linear control approaches such as LQR control, predictive control, or Model Predictive Control (MPC). The paper demonstrates the approach using the ELectrified Vehicle library for sImulation and Optimization (ELVIO). It is an open-source MATLAB/Simulink library designed for the quick and easy simulation and optimization of different powertrain and drivetrain architectures. It follows a modelling methodology that combines backward-facing and forward-facing signal path, which means that no driver model is required. The results show that the approximated solution provides a performance that is very close to the solution of the original problem except for extreme parts of the operating range (in which case the solution tends to be driven by constraints anyway).
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