Asymptotics of Some Nonlinear Eigenvalue Problems for a
... was shown that the effect of the fringing-field is to reduce the pull-in voltage. In addition, it was shown qualitatively in [21] that the effect of the fringing-field is to destroy the infinite fold point structure of the basic membrane problem (1.2) in the unit disk. Another simple modification of ...
... was shown that the effect of the fringing-field is to reduce the pull-in voltage. In addition, it was shown qualitatively in [21] that the effect of the fringing-field is to destroy the infinite fold point structure of the basic membrane problem (1.2) in the unit disk. Another simple modification of ...
Practice Problems For Final Math 5B
... plane is ~v = (1, 2, −1). We can get a second tangent vector by finding the vector between (−3, −2, −2) and (1, 0, 3). So let w ~ = (4, 2, 5). Then ~v × w ~ = ~i(10 + 2) − ~j(5 + 4) + ~k(2 − 8) = (12, −9, −6). So we can choose ~n = (4, −3, −2) and our plane has the form 4x − 3y − 2z = d. Plugging in ...
... plane is ~v = (1, 2, −1). We can get a second tangent vector by finding the vector between (−3, −2, −2) and (1, 0, 3). So let w ~ = (4, 2, 5). Then ~v × w ~ = ~i(10 + 2) − ~j(5 + 4) + ~k(2 − 8) = (12, −9, −6). So we can choose ~n = (4, −3, −2) and our plane has the form 4x − 3y − 2z = d. Plugging in ...
Swarm Intelligence based Soft Computing Techniques for the
... optimization) in general. It means that one objective is optimized at the cost of other objective. The multi objective optimization problems are difficult but realistic, because of their broad applicability, optimization problems have been studied by researchers with various backgrounds. This gives ...
... optimization) in general. It means that one objective is optimized at the cost of other objective. The multi objective optimization problems are difficult but realistic, because of their broad applicability, optimization problems have been studied by researchers with various backgrounds. This gives ...
Generalised Integer Programming Based on Logically Defined
... In this paper, we consider a class of generalised integer programming problems where the variable domains are finite (but not restricted to be 2-valued); and the constraints are allowed to be taken from a set of logically defined relations. The set of relations that we consider is based on regular s ...
... In this paper, we consider a class of generalised integer programming problems where the variable domains are finite (but not restricted to be 2-valued); and the constraints are allowed to be taken from a set of logically defined relations. The set of relations that we consider is based on regular s ...
The x
... 1. Determine the values of x for which f ″is zero or where f ″ is not defined, and identify the open intervals determined by these numbers. 2. Determine the sign of f ″ in each interval found in step 1. To do this compute f ″(c), where c is any conveniently chosen test number in the interval. a. If ...
... 1. Determine the values of x for which f ″is zero or where f ″ is not defined, and identify the open intervals determined by these numbers. 2. Determine the sign of f ″ in each interval found in step 1. To do this compute f ″(c), where c is any conveniently chosen test number in the interval. a. If ...
Aligning two sequences within a specified diagonal band
... requirement to ‘‘start at the beginning, end at the end’’ is reflected in the L ≤ min(0, N − M) and U ≥ max(0, N − M) constraints. ‘‘Local’’ sequence alignments do not require that the beginning and end of the alignment correspond to the beginning and end of the sequence (i.e., the aligned sequences ...
... requirement to ‘‘start at the beginning, end at the end’’ is reflected in the L ≤ min(0, N − M) and U ≥ max(0, N − M) constraints. ‘‘Local’’ sequence alignments do not require that the beginning and end of the alignment correspond to the beginning and end of the sequence (i.e., the aligned sequences ...
Plea for a semidefinite optimization solver in complex numbers
... This paper is not at such a high level of generality but demonstrates that a semidefinite optimization (SDO) problem, naturally or possibly defined in complex numbers, should most often also be solved by an SDO solver in complex numbers, if computing time prevails. We are even more specific, since ...
... This paper is not at such a high level of generality but demonstrates that a semidefinite optimization (SDO) problem, naturally or possibly defined in complex numbers, should most often also be solved by an SDO solver in complex numbers, if computing time prevails. We are even more specific, since ...
Information Gathering and Reward Exploitation of Subgoals for
... Point-based Solvers Information gathering in large state spaces and planning with long sequences of actions are two major challenges for planning in large POMDPs. Point-based approximations are among the most successful approaches to approximate the value function in large POMDPs. Solutions are comp ...
... Point-based Solvers Information gathering in large state spaces and planning with long sequences of actions are two major challenges for planning in large POMDPs. Point-based approximations are among the most successful approaches to approximate the value function in large POMDPs. Solutions are comp ...
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
... Genetic algorithm is modified to introduce operators like simulated binary crossover (SBX) and blend crossover (BLX). The mutation process is also completed through polynomial function. The process so formed is called self adaptive real coded genetic algorithm [26]. Adaptive Genetic algorithm based ...
... Genetic algorithm is modified to introduce operators like simulated binary crossover (SBX) and blend crossover (BLX). The mutation process is also completed through polynomial function. The process so formed is called self adaptive real coded genetic algorithm [26]. Adaptive Genetic algorithm based ...
Seven Challenges in Parallel SAT Solving
... may be considered inferior to a solver that performs efficiently, even if its speedup figure is smaller. We expect this will be the case for many software and hardware verification applications in the near future, where limited size clusters are used to verify designs overnight. In the second catego ...
... may be considered inferior to a solver that performs efficiently, even if its speedup figure is smaller. We expect this will be the case for many software and hardware verification applications in the near future, where limited size clusters are used to verify designs overnight. In the second catego ...
Constant-Time LCA Retrieval
... We can instead apply Procedure I to each of these loglogn subset which would total the space and time complexity of the whole algorithm to O( nloglogn ). If we choose to further partition these subset into subsets of size logloglogn, we would reach O(nlogloglogn). We can continue in this fashion for ...
... We can instead apply Procedure I to each of these loglogn subset which would total the space and time complexity of the whole algorithm to O( nloglogn ). If we choose to further partition these subset into subsets of size logloglogn, we would reach O(nlogloglogn). We can continue in this fashion for ...
Travelling salesman problem
The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.TSP is a special case of the travelling purchaser problem and the Vehicle routing problem.In the theory of computational complexity, the decision version of the TSP (where, given a length L, the task is to decide whether the graph has any tour shorter than L) belongs to the class of NP-complete problems. Thus, it is possible that the worst-case running time for any algorithm for the TSP increases superpolynomially (perhaps, specifically, exponentially) with the number of cities.The problem was first formulated in 1930 and is one of the most intensively studied problems in optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally difficult, a large number of heuristics and exact methods are known, so that some instances with tens of thousands of cities can be solved completely and even problems with millions of cities can be approximated within a small fraction of 1%.The TSP has several applications even in its purest formulation, such as planning, logistics, and the manufacture of microchips. Slightly modified, it appears as a sub-problem in many areas, such as DNA sequencing. In these applications, the concept city represents, for example, customers, soldering points, or DNA fragments, and the concept distance represents travelling times or cost, or a similarity measure between DNA fragments. The TSP also appears in astronomy, as astronomers observing many sources will want to minimise the time spent slewing the telescope between the sources. In many applications, additional constraints such as limited resources or time windows may be imposed.