谈中考数列型试题命制中的几个问题

举例剖析数列型中考试题命制中的“规律不唯一”、“表述不明确”、“结论不存在”等问题，并提出命题对策：利用多项约束，使试题表述清晰、规范、到位．

Stabilizability analysis of sphere plants

Let P（s, δ） be a sphere plant family described by the transfer function set where the coefficients of the denominator and numerator polynomials are affine in a real uncertain parameter vector δ satisfying the Euclidean norm constraint ｜｜δ｜｜〈δ. The concept of stabilizability radius of P（s, δ） is introduced which is the norm bound δs for δ such that every member plant of P（s, δ） is stabilizable if and only if ｜｜δ｜｜〈δs. The stabilizability radius can be simply interpreted as the ＇largest sphere＇ around the nominal plant P（s,θ） such that P（s, δ） is stabilizable. The numerical method and the analytical method are presented to solve the stabilizability radius calculation problem of the sphere plants.

Solution to the Balanced Academic Curriculum Problem Using Tabu Search

The Balanced Academic Curriculum Problem （BACP） is a constraint satisfaction problem classified as （Non-deterministic Polynomial-time Hard） NP-Hard. This problem consists in the allocation of courses in the periods that are part of a curriculum such that the prerequisites are satisfied and the load of courses is balanced for the students. This paper presents the solution for a modified BACP where the academic loads and number of curses may be the same or different for each one of the periods and allows having some courses in a specific period. This problem is modeled as an integer programming problem and is proposed the use of Tabu search with short-term memory for its solution because it is not possible to find solutions for all the instances of this modified problem with an exact method.

Layered heuristic algorithm for multiple restriction routes

A layered algorithm by bidirectional searching is proposed in this paper to solve the problem that it is difficult and time consuming to reach an optimal solution of the route search with multiple parameter restrictions for good quality of service. Firstly, a set of reachable paths to each intermediate node from the source node and the sink node based on adjacent matrix transformation are calculated respectively. Then a temporal optimal path is selected by adopting the proposed heuristic method according to a non-linear cost function. When the total number of the accumulated nodes by bidirectional searching reaches n-2, the paths from two directions to an intermediate node should be combined and several paths via different nodes from the source node to the sink node can be obtained, then an optimal path in the whole set of paths can be taken as the output route. Some simulation examples are included to show the effectiveness and efficiency of the proposed method. In addition, the proposed algorithm can be implemented with parallel computation and thus, the new algorithm has better performance in time complexity than other algorithms. Mathematical analysis indicates that the maximum complexity in time, based on parallel computation, is the same as the polynomial complexity of O(kn2-3kn+k), and some simulation results are shown to support this analysis.

MINIMIZING A LINEAR FRACTIONAL FUNCTION SUBJECT TO A SYSTEM OF SUP-T EQUATIONS WITH A CONTINUOUS ARCHIMEDEAN TRIANGULAR NORM

This paper shows that the problem of minimizing a linear fractional function subject to asystem of sup-T equations with a continuous Archimedean triangular norm T can be reduced to a 0-1linear fractional optimization problem in polynomial time.Consequently,parametrization techniques,e.g.,Dinkelbach's algorithm,can be applied by solving a classical set covering problem in each iteration.Similar reduction can also be performed on the sup-T equation constrained optimization problems withan objective function being monotone in each variable separately.This method could be extended aswell to the case in which the triangular norm is non-Archimedean.

Equality-constrained minimization of polynomial functions

This paper investigates the equality-constrained minimization of polynomial functions. Let R be the field of real numbers, and R[x1,..., xn] the ring of polynomials over R in variables x1,..., xn. For an f ∈ R[x1,..., xn] and a finite subset H of R[x1,..., xn], denote by V(f : H) the set {f( ˉα) | ˉα∈ Rn, and h( ˉα) =0, ? h ∈ H}. We provide an effective algorithm for computing a finite set U of non-zero univariate polynomials such that the infimum inf V(f : H) of V(f : H) is a root of some polynomial in U whenever inf V(f : H) = ±∞.The strategies of this paper are decomposing a finite set of polynomials into triangular chains of polynomials and computing the so-called revised resultants. With the aid of the computer algebraic system Maple, our algorithm has been made into a general program to treat the equality-constrained minimization of polynomials with rational coefficients.