关于同顺序m×n排序问题中总工时下界的一种简便算法

本文对越民义、韩继业《同顺序m×n排序问题的一个新方法》(见《科学通报》1979,18,pp.821~824)一文关于下界B(S…S″)的算法中需大量反复计算的t_m-1m(R_m.)给出了一种简便算法,同时,又对其所提出的下界B(S…S′)的算法作了改进.从而提高了B(s…s′)的估值精度.     

金阳青椒西昌种植的生长特征分析及树势改良建议

西昌种植四年的金阳青椒总体性状表现良好，栽植第2～3年即开始挂果，树干、枝条的生长量较大，第一轮生枝条数平均达23枝；但是，由于管理技术欠缺的原因，主干枝抽枝过长，第二轮生枝条偏少，结果部位外移幅度大，内膛空间浪费，第一轮生枝条之间性状差异也较大；人工整形修剪，调整树势尤为必要。     

浅谈神东煤炭分公司安全生产管理与持续发展

通过对安全生产的分析,结合神东煤炭分公司安全生产管理模式,论证了安全生产管理与持续发展的关系。     

Optimization of capacity expansion planning for gas transportation networks

This paper presents techniques for solving the problem of minimizing investment costs on an existing gas transportation network. The goal of this program is to find, first, the optimal location of pipeline segments to be reinforced and, second, the optimal sizes (among a discrete commercial list of diameters) under the constraint of satisfaction of demands with high enough pressure for all users.     

Single machine scheduling with family setups to minimize total earliness and tardiness

This paper considers the problem of scheduling a given number of jobs on a single machine to minimize total earliness and tardiness when family setup times exist. The paper proposes optimal branch-and-bound algorithms for both the group technology assumption and if the group technology assumption is removed. A heuristic algorithm is proposed to solve larger problems with the group technology assumption removed. The proposed algorithms were empirically evaluated on problems of various sizes and parameters. The paper also explores how the choice of procedure affects total earliness and tardiness if an implementation of lean production methods has resulted in a reduction in setup times. An important finding of these empirical investigations is that scheduling jobs by removing the group technology assumption can significantly reduce total earliness and tardiness.     

Improving the efficiency of DC global optimization methods by improving the DC representation of the objective function

There are infinitely many ways of representing a d.c. function as a difference of convex functions. In this paper we analyze how the computational efficiency of a d.c.optimization algorithm depends on the representation we choose for the objective function, and we address the problem of characterizing and obtaining a computationally optimal representation. We introduce some theoretical concepts which are necessary for this analysis and report some numerical experiments.      

A proposal for a hybrid meta-strategy for combinatorial optimization problems

In this paper, we propose an algorithm named BDS (Bound-Driven Search) that combines features of exact and approximate methods. The proposed procedure may be seen as a local search algorithm that systematically explores (in a branch-and bound sense) the most promising nodes, thus preventing solutions from being reevaluated. Additionally, it can be regarded as an exact method as it may be able to guarantee that the solution found is optimal. We present the application of this new algorithm to a specific problem domain: the permutation flow shop scheduling problem with makespan objective. The subsequent computational experiments are encouraging, as the algorithm is able to yield exact or near exact solutions to most instances of the problem. Furthermore, the algorithm outperforms one of the best state-of-the-art algorithms for the problem.     

An acceleration of Erlenkotter-Körkel’s algorithms for the uncapacitated facility location problem

This contribution is focused on an acceleration of branch and bound algorithms for the uncapacitated facility location problem. Our approach is based on the well-known Erlenkotters’ procedures and Körkels’ multi-ascent and multi-adjustment algorithms, which have proved to be the efficient tools for solving the large-sized instances of the uncapacitated facility location problem. These two original approaches were examined and a thorough analysis of their performance revealed how each particular procedure contributes to the computational time of the whole algorithms. These analyses helped us to focus our effort on the most frequent procedures. The unique contribution of this paper is a new dual ascent procedure. This procedure leads to considerable acceleration of the lower bound computation process and reduces the resulting computational time. To demonstrate more efficient performance of amended algorithms we present the results of extensive numerical experiments.     

Two-stage integer programs with stochastic right-hand sides: a superadditive dual approach

We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides. We present an equivalent superadditive dual formulation that uses the value functions in both stages. We give two algorithms for finding the value functions. To solve the reformulation after obtaining the value functions, we develop a global branch-and-bound approach and a level-set approach to find an optimal tender. We show that our method can solve randomly generated instances whose extensive forms are several orders of magnitude larger than the extensive forms of those instances found in the literature. This work is supported by National Science Foundation grants DMI-0217190 and DMI-0355433.     

A novel algorithm for branch cut phase unwrapping

Branch cut method is a powerful noise-immune algorithm for correct phase unwrapping of noisy phase maps. The shortest branch cut length promises the optimal unwrapping result of the wrapped phase maps. A new algorithm is proposed to search for the shortest branch cut length by simple exchange operation. Although the algorithm is on the basis of stochastic search techniques, it has a high probability of finding the shortest branch cut length or an approximation of it. Compared with the traditional algorithms, the algorithm is fast and competitive.