A branch and cut algorithm for hub location problems with single assignment

The hub location problem with single assignment is the problem of locating hubs and assigning the terminal nodes to hubs in order to minimize the cost of hub installation and the cost of routing the traffic in the network. There may also be capacity restrictions on the amount of traffic that can transit by hubs. The aim of this paper is to investigate polyhedral properties of these problems and to develop a branch and cut algorithm based on these results.Acknowledgement The research of the first author was partially supported by the Banque Nationale de Belgique. The research of the second author was supported by France Telecom R&D under contract no. 99 1B 774. Their support is gratefully acknowledged.     

A restricted Lagrangean approach to the traveling salesman problem

We describe an algorithm for the asymmetric traveling salesman problem (TSP) using a new, restricted Lagrangean relaxation based on the assignment problem (AP). The Lagrange multipliers are constrained so as to guarantee the continued optimality of the initial AP solution, thus eliminating the need for repeatedly solving AP in the process of computing multipliers. We give several polynomially bounded procedures for generating valid inequalities and taking them into the Lagrangean function with a positive multiplier without violating the constraints, so as to strengthen the current lower bound. Upper bounds are generated by a fast tour-building heuristic. When the bound-strengthening techniques are exhausted without matching the upper with the lower bound, we branch by using two different rules, according to the situation: the usual subtour breaking disjunction, and a new disjunction based on conditional bounds. We discuss computational experience on 120 randomly generated asymmetric TSP's with up to 325 cities, the maximum time used for any single problem being 82 seconds. This is a considerable improvement upon earlier methods. Though the algorithm discussed here is for the asymmetric TSP, the approach can be adapted to the symmetric TSP by using the 2-matching problem instead of AP.Research supported by the National Science Foundation through grant no. MCS76-12026 A02 and the U.S. Office of Naval Research through contract no. N0014-75-C-0621 NR 047-048.     

Management of branch-duct intraductal papillary mucinous neoplasms of the pancreas: observation with MR imaging

Purpose

To evaluate the clinical outcomes of conservative management by observation with MRI of patients with branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs).

Materials and Methods

Twenty-three consecutive patients, who were followed up by MRI with magnetic resonance cholangiopancreatography (MRCP) over a period of more than 9 months after initial MRI examinations, were enrolled in this study. On MRI, number of lesions, the maximum diameter of BD-IPMNs, lesion location, the presence of associated dilatation of main pancreatic duct (MPD), the presence of enhancing mural nodules within the lesion and the presence of interval change were retrospectively reviewed on initial and follow-up MR images in consensus by two radiologists. All patients were evaluated to search for evidence of malignant progression of disease.

Results

The follow-up period ranged from 10 to 96 months (mean, 37 months). On initial MRI with MRCP, a total of 39 lesions were found in 23 patients. The maximum diameter of BD-IPMNs ranged between 6 and 32 mm, with a mean of 12 mm. Thirty-four lesions (87%) of 19 patients remained unchanged in the maximum diameter. Five lesions (13%) of four patients showed an increase in the maximum diameter. Enhancing mural nodules were not found in any individual, neither on the initial MRI study nor on the follow-up studies. There was no patient who had evidence of local aggressive growth of tumor or evidence of metastases to distant sites.

Conclusion

Our study suggests that branch-duct IPMNs without enhancing mural nodules are essentially benign and should be managed nonoperatively through observation by MRI.     

线性比式和规划问题的输出空间分支定界算法

本文旨在针对线性比式和规划这一NP-Hard非线性规划问题提出新的全局优化算法.首先,通过引入p个辅助变量把原问题等价的转化为一个非线性规划问题,这个非线性规划问题的目标函数是乘积和的形式并给原问题增加了p个新的非线性约束,再通过构造凸凹包络的技巧对等价问题的目标函数和约束条件进行相应的线性放缩,构成等价问题的一个下界线性松弛规划问题,从而提出了一个求解原问题的分支定界算法,并证明了算法的收敛性.最后,通过数值结果比较表明所提出的算法是可行有效的.     

On diagonal actions of branch groups and the corresponding characters

We introduce notions of absolutely non-free and perfectly non-free group actions and use them to study the associated unitary representations. We show that every weakly branch group acting on a regular rooted tree acts absolutely non-freely on the boundary of the tree. Using this result and the symmetrized diagonal actions we construct for every countable branch group infinitely many different ergodic perfectly non-free actions, infinitely many II₁-factor representations, and infinitely many continuous ergodic invariant random subgroups.     

On globally solving the extended trust-region subproblems

With the help of the newly developed technique—second order cone (SOC) constraints to strengthen the SDP relaxation of the extended trust-region subproblem (eTRS), we modify two recent SDP relaxation based branch and bound algorithms for solving eTRS. Numerical experiments on some types of problems show that the new algorithms run faster for finding the global optimal solutions than the SDP relaxation based algorithms.     

A branch and cut algorithm for the hierarchical network design problem

The Hierarchical Network Design Problem consists of locating a minimum cost bi-level network on a graph. The higher level sub-network is a path visiting two or more nodes. The lower level sub-network is a forest connecting the remaining nodes to the path. We optimally solve the problem using an ad hoc branch and cut procedure. Relaxed versions of a base model are solved using an optimization package and, if binary variables have fractional values or if some of the relaxed constraints are violated in the solution, cutting planes are added. Once no more cuts can be added, branch and bound is used. The method for finding valid cutting planes is presented. Finally, we use different available test instances to compare the procedure with the best known published optimal procedure, with good results. In none of the instances we needed to apply branch and bound, but only the cutting planes.     

A multi-level search strategy for the 0-1 Multidimensional Knapsack Problem

We propose an exact method based on a multi-level search strategy for solving the 0-1 Multidimensional Knapsack Problem. Our search strategy is primarily based on the reduced costs of the non-basic variables of the LP-relaxation solution. Considering that the variables are sorted in decreasing order of their absolute reduced cost value, the top level branches of the search tree are enumerated following Resolution Search strategy, the middle level branches are enumerated following Branch & Bound strategy and the lower level branches are enumerated according to a simple Depth First Search enumeration strategy. Experimentally, this cooperative scheme is able to solve optimally large-scale strongly correlated 0-1 Multidimensional Knapsack Problem instances. The optimal values of all the 10 constraint, 500 variable instances and some of the 30 constraint, 250 variable instances of the OR-Library were found. These values were previously unknown.     

On single processor scheduling problems with learning dependent on the number of processed jobs

The importance of the role that learning plays in manufacturing, industry and computer systems is undeniable as well as the profit that can be increased if this phenomenon is taken into consideration for short- and long-term optimization. In this paper, we focus on scheduling jobs on a single processor, where its effectiveness can increase with the number of processed jobs, to minimize one of the following objectives: the maximum completion time with the release dates, the maximum lateness and the number of late jobs. It is proved that these well known polynomially solvable problems become at least NP-hard with the considered learning models. To solve them we provide some elimination procedures that are used to construct a branch and bound algorithm. Furthermore, we propose some fast heuristics for the problem of minimizing the number of late jobs with the general model of the learning effect.     

An enumeration procedure for the assembly line balancing problem based on branching by non-decreasing idle time

In this article, we present a new exact algorithm for solving the simple assembly line balancing problem given a determined cycle time (SALBP-1). The algorithm is a station-oriented bidirectional branch-and-bound procedure based on a new enumeration strategy that explores the feasible solutions tree in a non-decreasing idle time order. The procedure uses several well-known lower bounds, dominance rules and a new logical test based on the assimilation of the feasibility problem for a given cycle time and number of stations (SALBP-F) to a maximum-flow problem.