pse14 VanLong 19108260 en
... generations to enjoy higher levels of consumption. But, a priori, a trajectory where the lowest levels of consumption are in the far future cannot be excluded either, for it is admissible. However, Theorem 3 establishes that this possiblity does not characterize a solution to the MBR problem. The ne ...
... generations to enjoy higher levels of consumption. But, a priori, a trajectory where the lowest levels of consumption are in the far future cannot be excluded either, for it is admissible. However, Theorem 3 establishes that this possiblity does not characterize a solution to the MBR problem. The ne ...
Differential Equations
... that are lost in the more recent generation of texts. I am also planning to consult the texts by Rice & Strange, Zill, Edwards & Penny , Finney and Ostberg, Coddington, Arnold, Zachmanoglou and Thoe, Hille, Ince, Blanchard-Devaney and Hall, Martin, Campbell as well as others I’ll add to this list on ...
... that are lost in the more recent generation of texts. I am also planning to consult the texts by Rice & Strange, Zill, Edwards & Penny , Finney and Ostberg, Coddington, Arnold, Zachmanoglou and Thoe, Hille, Ince, Blanchard-Devaney and Hall, Martin, Campbell as well as others I’ll add to this list on ...
Stochastic Search and Surveillance Strategies for
... Mixed human-robot teams are becoming increasingly important in complex and information rich systems. The purpose of the mixed teams is to exploit the human cognitive abilities in complex missions. It has been evident that the information overload in these complex missions has a detrimental effect on ...
... Mixed human-robot teams are becoming increasingly important in complex and information rich systems. The purpose of the mixed teams is to exploit the human cognitive abilities in complex missions. It has been evident that the information overload in these complex missions has a detrimental effect on ...
Availability-aware Mapping of Service Function Chains
... U ptime + Downtime M T BF + M T T R 2) Availability of composed system: An SFC is generally composed of a number of VNFs. In order to estimate the availability of such composite system, which is derived from the individual components it consists of, two basic ways of combining components, serial and ...
... U ptime + Downtime M T BF + M T T R 2) Availability of composed system: An SFC is generally composed of a number of VNFs. In order to estimate the availability of such composite system, which is derived from the individual components it consists of, two basic ways of combining components, serial and ...
Recursion
... directly or indirectly – direct recursion - function is invoked by a statement in its own body – indirect recursion - one function initiates a sequence of function invocations that eventually invokes the original ...
... directly or indirectly – direct recursion - function is invoked by a statement in its own body – indirect recursion - one function initiates a sequence of function invocations that eventually invokes the original ...
“relations constraints” on lifting variables + SDP Relaxation Question
... Relaxations of higher order incorporate the inequality constraints in LMI • We show relaxation of order 2 • It is possible to continue and apply relaxations • Theory guarantees convergence to global optimum ...
... Relaxations of higher order incorporate the inequality constraints in LMI • We show relaxation of order 2 • It is possible to continue and apply relaxations • Theory guarantees convergence to global optimum ...
Dynamic right-sizing for power-proportional data centers
... A promising approach for making data centers more powerproportional is using software to dynamically adapt the number of active servers to match the current workload, i.e., to dynamically ‘right-size’ the data center. Specifically, dynamic right-sizing refers to adapting the way requests are dispatc ...
... A promising approach for making data centers more powerproportional is using software to dynamically adapt the number of active servers to match the current workload, i.e., to dynamically ‘right-size’ the data center. Specifically, dynamic right-sizing refers to adapting the way requests are dispatc ...
Pareto Optimal Solutions Visualization Techniques for Multiobjective
... solution with precision between 0.949 and 1.486 that would have some acceptable level of residual precision and error detectability. Increasing the maximum desired value of the reference objective does not guarantee that candidate solutions with acceptable capabilities for all properties will be obt ...
... solution with precision between 0.949 and 1.486 that would have some acceptable level of residual precision and error detectability. Increasing the maximum desired value of the reference objective does not guarantee that candidate solutions with acceptable capabilities for all properties will be obt ...
Contest File (2016)
... which has two solutions, x = 3 and x = 1. Now consider the equation g(f (x)) = 0: g(x) has one root at 2, so f (x) = 2, which implies that x √ = b2 . Therefore, in order for the equation f (g(x)) = g(f (x)) = 0 to have exactly one solution, b must equal 3. Problem 3. ...
... which has two solutions, x = 3 and x = 1. Now consider the equation g(f (x)) = 0: g(x) has one root at 2, so f (x) = 2, which implies that x √ = b2 . Therefore, in order for the equation f (g(x)) = g(f (x)) = 0 to have exactly one solution, b must equal 3. Problem 3. ...
Document
... Algorithms based on recurrence Algorithmic scheme: • Reduce the input to smaller sub-input(s) • Solve the problem for (some) sub-inputs • Merge the obtained solution(s) into one global solution ...
... Algorithms based on recurrence Algorithmic scheme: • Reduce the input to smaller sub-input(s) • Solve the problem for (some) sub-inputs • Merge the obtained solution(s) into one global solution ...
Pdf - Text of NPTEL IIT Video Lectures
... series approximation. Thus, we can write f (X) can be approximated equal to f (X 1) plus del f (X 1) T (X minus X 1). Similarly, we can write g j (X) is equal to approximately equal to g (X 1), g j (X 1) plus grad of g j (X 1) T, (X minus X 1). Similarly, h k can be written in the similar manner tha ...
... series approximation. Thus, we can write f (X) can be approximated equal to f (X 1) plus del f (X 1) T (X minus X 1). Similarly, we can write g j (X) is equal to approximately equal to g (X 1), g j (X 1) plus grad of g j (X 1) T, (X minus X 1). Similarly, h k can be written in the similar manner tha ...
A multi-phase algorithm for a joint lot
... and pricing problem with deterministic price-dependent demand. However, in many settings, to be realistic, demands over a planning cycle should also be treated as uncertain. Therefore, we extend the problem in their paper to consider stochastic demands. For many consumer durable products, capacity c ...
... and pricing problem with deterministic price-dependent demand. However, in many settings, to be realistic, demands over a planning cycle should also be treated as uncertain. Therefore, we extend the problem in their paper to consider stochastic demands. For many consumer durable products, capacity c ...
Interconnect Layout Optimization Under Higher
... Find: An optimal wire width assignment to minimize weighted sum of sink delays ...
... Find: An optimal wire width assignment to minimize weighted sum of sink delays ...
Transportation problem
... The transportation problem seeks the determination of a minimum cost transportation plan for a single commodity from a number of sources to a number of destinations. It requires the specification of the level of supply at each source, the amount of demand at each destination, and the transportation ...
... The transportation problem seeks the determination of a minimum cost transportation plan for a single commodity from a number of sources to a number of destinations. It requires the specification of the level of supply at each source, the amount of demand at each destination, and the transportation ...
![[SE4] Integral simplex using decomposition for the set partitioning](http://s1.studyres.com/store/data/019693331_1-53981937bc1c58ca78e99eb6a82baf81-300x300.png)
[SE4] Integral simplex using decomposition for the set partitioning
... algorithm. We discuss the relationships between the combinations of variables generated by the complementary problem of IPS and the minimal sets of Balas and Padberg (1975). We present the conditions to be added to the complementary problems to obtain combinations of columns that permit us to move f ...
... algorithm. We discuss the relationships between the combinations of variables generated by the complementary problem of IPS and the minimal sets of Balas and Padberg (1975). We present the conditions to be added to the complementary problems to obtain combinations of columns that permit us to move f ...
Multi-Objective Optimization Using Genetic Algorithms
... objectives. Therefore, GA has been the most popular heuristic approach to multi-objective design and optimization problems. Jones et al. [25] reported that 90% of the approaches to multiobjective optimization aimed to approximate the true Pareto front for the underlying problem. A majority of these ...
... objectives. Therefore, GA has been the most popular heuristic approach to multi-objective design and optimization problems. Jones et al. [25] reported that 90% of the approaches to multiobjective optimization aimed to approximate the true Pareto front for the underlying problem. A majority of these ...
NWERC 2015 Presentation of solutions
... If x, y appear in different order in two permutations π, φ, we call this an inversion of π and φ. If x, y appear in the same order everywhere, they don’t form any inversions. If x, y do not appear in the same order, they form exactly two inversions: two permutations agree while the third one is diff ...
... If x, y appear in different order in two permutations π, φ, we call this an inversion of π and φ. If x, y appear in the same order everywhere, they don’t form any inversions. If x, y do not appear in the same order, they form exactly two inversions: two permutations agree while the third one is diff ...
A Survey of Partially Observable Markov Decision Processes
... differently. In some models an observation is taken and then the transition to the new state is made. In this presentation, movement in the chain is followed by an observation. Although the formula for updating the information vector, eqn. (2.2), may be slightly different, the two views are equivale ...
... differently. In some models an observation is taken and then the transition to the new state is made. In this presentation, movement in the chain is followed by an observation. Although the formula for updating the information vector, eqn. (2.2), may be slightly different, the two views are equivale ...
Algorithm GENITOR
... signals that reach the next Si stations. Note that Si is a r.v. dependent on power and availability of retransmitter amplifiers. The aim of the system is to provide propagation of a signal from transmitter to receiver. The LMCCS was first introduced by Hwang & Yao [1] as a generalization of linear ...
... signals that reach the next Si stations. Note that Si is a r.v. dependent on power and availability of retransmitter amplifiers. The aim of the system is to provide propagation of a signal from transmitter to receiver. The LMCCS was first introduced by Hwang & Yao [1] as a generalization of linear ...
Download paper (PDF)
... An outline of the remainder of the paper, and a summary of our main results are as follows: In the next section, we provide the model and a description of the problems studied. For the objectives considered here, the relevant state variable is the ratio of the investor’s wealth to the benchmark. Sin ...
... An outline of the remainder of the paper, and a summary of our main results are as follows: In the next section, we provide the model and a description of the problems studied. For the objectives considered here, the relevant state variable is the ratio of the investor’s wealth to the benchmark. Sin ...
Multiuser MISO Beamforming for Simultaneous
... the EH receivers (e.g., sensors and other low-power devices) are deployed sufficiently close to the AP, while the ID receivers (e.g., tablet, cell phone and laptop) can be located more distant from the AP. Notice that the proposed transmission scheme resolves the mismatched power issue for EH and ID ...
... the EH receivers (e.g., sensors and other low-power devices) are deployed sufficiently close to the AP, while the ID receivers (e.g., tablet, cell phone and laptop) can be located more distant from the AP. Notice that the proposed transmission scheme resolves the mismatched power issue for EH and ID ...
A Market-Based Study of Optimal ATM`S Deployment Strategy
... appears to be deficient in finding the best solution and it usually falls in local minima. Coming to the second proposed technique, (RGAC) increases the search efficiency by improving the evolutionary process while meeting a feasible solution. Moreover, RGAC has proved to be a robust approach for so ...
... appears to be deficient in finding the best solution and it usually falls in local minima. Coming to the second proposed technique, (RGAC) increases the search efficiency by improving the evolutionary process while meeting a feasible solution. Moreover, RGAC has proved to be a robust approach for so ...
Aligning two sequences within a specified diagonal band
... B′ of B are found, which can be done by any of several available methods, then a global alignment procedure is called with A′ and B′. Appropriate values of L′ and U′ for the global problem are inferred from the L and U of the local problems. In other situations, a method to find unconstrained local ...
... B′ of B are found, which can be done by any of several available methods, then a global alignment procedure is called with A′ and B′. Appropriate values of L′ and U′ for the global problem are inferred from the L and U of the local problems. In other situations, a method to find unconstrained local ...
Document
... The penalty incurred by additional space in a gap decrease as the gap gets longer. Example: the logarithmic gap penalty g(q) = a log q + b ...
... The penalty incurred by additional space in a gap decrease as the gap gets longer. Example: the logarithmic gap penalty g(q) = a log q + b ...
Dynamic programming
In mathematics, computer science, economics, and bioinformatics, dynamic programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems. It is applicable to problems exhibiting the properties of overlapping subproblems and optimal substructure (described below). When applicable, the method takes far less time than other methods that don't take advantage of the subproblem overlap (like depth-first search).In order to solve a given problem using a dynamic programming approach, we need to solve different parts of the problem (subproblems), then combine the solutions of the subproblems to reach an overall solution. Often when using a more naive method, many of the subproblems are generated and solved many times. The dynamic programming approach seeks to solve each subproblem only once, thus reducing the number of computations: once the solution to a given subproblem has been computed, it is stored or ""memoized"": the next time the same solution is needed, it is simply looked up. This approach is especially useful when the number of repeating subproblems grows exponentially as a function of the size of the input.Dynamic programming algorithms are used for optimization (for example, finding the shortest path between two points, or the fastest way to multiply many matrices). A dynamic programming algorithm will examine the previously solved subproblems and will combine their solutions to give the best solution for the given problem. The alternatives are many, such as using a greedy algorithm, which picks the locally optimal choice at each branch in the road. The locally optimal choice may be a poor choice for the overall solution. While a greedy algorithm does not guarantee an optimal solution, it is often faster to calculate. Fortunately, some greedy algorithms (such as minimum spanning trees) are proven to lead to the optimal solution.For example, let's say that you have to get from point A to point B as fast as possible, in a given city, during rush hour. A dynamic programming algorithm will look at finding the shortest paths to points close to A, and use those solutions to eventually find the shortest path to B. On the other hand, a greedy algorithm will start you driving immediately and will pick the road that looks the fastest at every intersection. As you can imagine, this strategy might not lead to the fastest arrival time, since you might take some ""easy"" streets and then find yourself hopelessly stuck in a traffic jam.Sometimes, applying memoization to a naive basic recursive solution already results in a dynamic programming solution with asymptotically optimal time complexity; however, the optimal solution to some problems requires more sophisticated dynamic programming algorithms. Some of these may be recursive as well but parametrized differently from the naive solution. Others can be more complicated and cannot be implemented as a recursive function with memoization. Examples of these are the two solutions to the Egg Dropping puzzle below.