Effect of the subdivision strategy on convergence and efficiency of some global optimization algorithms

We investigate subdivision strategies that can improve the convergence and efficiency of some branch and bound algorithms of global optimization. In particular, a general class of so called weakly exhaustive simplicial subdivision processes is introduced that subsumes all previously known radial exhaustive processes. This result provides the basis for constructing flexible subdivision strategies that can be adapted to take advantage of various problem conditions.     

Pure adaptive search in monte carlo optimization

Pure adaptive search constructs a sequence of points uniformly distributed within a corresponding sequence of nested regions of the feasible space. At any stage, the next point in the sequence is chosen uniformly distributed over the region of feasible space containing all points that are equal or superior in value to the previous points in the sequence. We show that for convex programs the number of iterations required to achieve a given accuracy of solution increases at most linearly in the dimension of the problem. This compares to exponential growth in iterations required for pure random search.     

Route stability in vehicle routing decisions: a bi-objective approach using metaheuristics

In this paper, we argue that vehicle routing solutions are often tactical decisions, that should not be changed too often or too much. For marketing or other reasons, vehicle routing solutions should be stable, i.e. a new solution (when e.g. new customers require service) should be as similar as possible to a solution already in use. Simultaneously however, this new solution should still have a good quality in the traditional sense (e.g. small total travel cost). In this paper, we develop a way to measure the difference between two vehicle routing solutions. We use this distance measure to create a metaheuristic approach that will find solutions that are “close” (in the solution space) to a given baseline solution and at the same time have a high quality in the sense that their total distance traveled is small. By using this approach, the dispatcher is offered a choice of Pareto-optimal solutions, allowing him to make a trade-off between changing his existing solution and allowing a longer travel distance. Some experiments are performed to show the effectiveness of the approach.     

原木随机存贮策略的最优化问题

本主要介绍原木经销商在周期内原木变价销售情况下的最佳期初贮存量的决策方法，在建立期望机会成本的数学模型基础上，探讨原木随机存贮策略的最优化问题。     

Efficient domain partitioning algorithms for global optimization of rational and Lipschitz continuous functions

A domain partitioning algorithm for minimizing or maximizing a Lipschitz continuous function is enhanced to yield two new, more efficient algorithms. The use of interval arithmetic in the case of rational functions and the estimates of Lipschitz constants valid in subsets of the domain in the case of others and the addition of local optimization have resulted in an algorithm which, in tests on standard functions, performs well.     

The Cross-Entropy Method for Continuous Multi-Extremal Optimization

In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.      

A result on sets,with applications to vector optimization

In this paper there is stated a result on sets in ordered linear spaces which can be used to show that some properties of the sets are inherited by their convex hulls under suitable conditions. As applications one gives a characterization of weakly efficient points and a duality result for nonconvex vector optimization problems.     

On the S-procedure and Some Variants

We give a concise review and extension of S-procedure that is an instrumental tool in control theory and robust optimization analysis. We also discuss the approximate S-Lemma as well as its applications in robust optimization.The many suggestions and detailed corrections of an anonymous referee are gratefully acknowledged.     

Al12N、Al12B团簇结构和电子性质的密度泛函计算

利用密度泛函理论研究了Al12N和Al12B团簇的原子结构和电子性质,通过各种异构体的比较,发现两种掺杂团簇的最低能量结构都是完好的二十面体(Ih)结构,N(B)原子占据在二十面体的中心.高对称性团簇形成稀疏离散的电子态密度和大的电子能隙.在Al-N之间发生较大的电荷转移.因此我们建议把Al12N团簇看作是碱金属超原子,Al12B团簇看作是卤素超原子,用来构造团簇组装固体.     

Some effective methods for unconstrained optimization based on the solution of systems of ordinary differential equations

In this paper, we review briefly some methods for minimizing a functionF(x), which proceed by follwoing the solution curve of a system of ordinary differential equations. Such methods have often been thought to be unacceptably expensive; but we show, by means of extensive numerical tests, using a variety of algorithms, that the ODE approach can in fact be implemented in such a way as to be more than competitive with currently available conventional techniques.This work was supported by a SERC research studentship for the first author. Both authors are indebted to Dr. J. J. McKeown and Dr. K. D. Patel of SCICON Ltd, the collaborating establishment, for their advice and encouragement.