Exploring strategy use and strategy flexibility in non
... Elia in press). Therefore, non-routine problems are considered more complicated and difficult than routine problems. However, Polya observed that, although routine problems can be used to fulfill particular didactical functions of teaching students to apply a certain procedure or a definition correc ...
... Elia in press). Therefore, non-routine problems are considered more complicated and difficult than routine problems. However, Polya observed that, although routine problems can be used to fulfill particular didactical functions of teaching students to apply a certain procedure or a definition correc ...
A Multidomain Discretization of the Richards Equation in Layered Soil
... We assume that the saturation and permeability functions are space-independent on each subdomain. Kirchhoff transformation of each subdomain problem separately then leads to a set of semi-linear equations, which can each be solved efficiently using monotone multigrid. The transformed subdomain probl ...
... We assume that the saturation and permeability functions are space-independent on each subdomain. Kirchhoff transformation of each subdomain problem separately then leads to a set of semi-linear equations, which can each be solved efficiently using monotone multigrid. The transformed subdomain probl ...
Informed RRT*: Optimal Sampling-based Path Planning Focused via
... b) Path Biasing: Path-biased sampling attempts to increase the frequency of sampling Xf by sampling around the current solution path. This assumes that the current solution is either homotopic to the optimum or separated only by small obstacles. As this assumption is not generally true, path-biasing ...
... b) Path Biasing: Path-biased sampling attempts to increase the frequency of sampling Xf by sampling around the current solution path. This assumes that the current solution is either homotopic to the optimum or separated only by small obstacles. As this assumption is not generally true, path-biasing ...
Mathematical Methods for Physics III (Hilbert Spaces)
... Property: A pre-Hilbert space is a normed space with the norm associated to the scalar product Definition: A Hilbert space is a pre-Hilbert space that is complete with the norm associated to the scalar product (rather the distance associated to the norm). ...
... Property: A pre-Hilbert space is a normed space with the norm associated to the scalar product Definition: A Hilbert space is a pre-Hilbert space that is complete with the norm associated to the scalar product (rather the distance associated to the norm). ...
nature of metacognition in a dynamic geometry
... (transitions). These episodes present periods of time during which a problem solver is engaged in a particular activity, such as exploring different possibilities or planning the best solution. Decision-making behaviors are analyzed by examining each episode and the transition between them using a s ...
... (transitions). These episodes present periods of time during which a problem solver is engaged in a particular activity, such as exploring different possibilities or planning the best solution. Decision-making behaviors are analyzed by examining each episode and the transition between them using a s ...
Transportation problems Transportation problems
... (If this is not possible then the solution is optimal.) 3 If the cost can be reduced by using a new route, as many units as possible are allocated to this new route to create a new solution. 4 The new solution is checked in the same way as the initial solution to see if it is optimal. If not, any ne ...
... (If this is not possible then the solution is optimal.) 3 If the cost can be reduced by using a new route, as many units as possible are allocated to this new route to create a new solution. 4 The new solution is checked in the same way as the initial solution to see if it is optimal. If not, any ne ...
Seven common errors in finding exact solutions of
... In this section we start to discuss common errors to search for the exact solutions of nonlinear differential equations. We observed these errors by studying many papers in the last years. Many authors try to introduce ”new methods” to look for ”new solutions” of nonlinear differential equations and ...
... In this section we start to discuss common errors to search for the exact solutions of nonlinear differential equations. We observed these errors by studying many papers in the last years. Many authors try to introduce ”new methods” to look for ”new solutions” of nonlinear differential equations and ...
Multiple-criteria decision analysis
Multiple-criteria decision-making or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly considers multiple criteria in decision-making environments. Whether in our daily lives or in professional settings, there are typically multiple conflicting criteria that need to be evaluated in making decisions. Cost or price is usually one of the main criteria. Some measure of quality is typically another criterion that is in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider. It is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, we are interested in getting high returns but at the same time reducing our risks. Again, the stocks that have the potential of bringing high returns typically also carry high risks of losing money. In a service industry, customer satisfaction and the cost of providing service are two conflicting criteria that would be useful to consider.In our daily lives, we usually weigh multiple criteria implicitly and we may be comfortable with the consequences of such decisions that are made based on only intuition. On the other hand, when stakes are high, it is important to properly structure the problem and explicitly evaluate multiple criteria. In making the decision of whether to build a nuclear power plant or not, and where to build it, there are not only very complex issues involving multiple criteria, but there are also multiple parties who are deeply affected from the consequences.Structuring complex problems well and considering multiple criteria explicitly leads to more informed and better decisions. There have been important advances in this field since the start of the modern multiple-criteria decision-making discipline in the early 1960s. A variety of approaches and methods, many implemented by specialized decision-making software, have been developed for their application in an array of disciplines, ranging from politics and business to the environment and energy.