An assumption-free convergence analysis for a perturbation of the scaling algorithm for linear programs,with application to the L1 estimation problem

This article is concerned with the scaling variant of Karmarkar's algorithm for linear programming problems. Several researchers have presented convergence analyses for this algorithm under various nondegeneracy types of assumptions, or under assumptions regarding the nature of the sequence of iterates generated by the algorithm. By employing a slight perturbation of the algorithm, which is computationally imperceptible, we are able to prove without using any special assumptions that the algorithm converges finitely to an ε-optimal solution for any chosen ε > 0, from which it can be (polynomically) rounded to an optimum, for ε > 0 small enough. The logarithmic barrier function is used as a construct for this analysis. A rounding scheme which produces an optimal extreme point solution is also suggested. Besides the non-negatively constrained case, we also present a convergence analysis for the case of bounded variables. An application in statistics to the L₁ estimation problem and related computational results are presented.     

Book reviews

Red Banner: the Soviet Military System in Peace and War. By Christopher Donnelly. Jane's Information Group, Coulsdon, UK (1988), 288 pp., £35.00

Images of T. E. Lawrence. By S. E. Tabachnick and C. Matheson. Jonathan Cape, London (1988); The Letters of T. E. Lawrence. Edited by Malcolm Brown. Dent, London (1988); T. E. Lawrence. By J. Wilson. National Portrait Gallery Publications, London (1988); Lawrence and the Arab Revolts. By D. Nicolle. Osprey, London (1989)

Liddell Hart and the Weight of History. By John Mearsheimer. Brassey's, London (1989), £15.95

Science and Mythology in the Making of Defence Policy. Edited by Margaret Blunden and Owen Greene. Brassey's, London (1989), £27.50/$44.00

Warfare in the Twentieth Century. Edited by Colin McInnes and G. D. Sheffield. Unwin Hyman, London (1988), 239 pp., £25.00     

Benders' cuts guided large neighborhood search for the traveling umpire problem

This article introduces the use of Benders' cuts to guide a large neighborhood search to solve the traveling umpire problem, a sports scheduling problem inspired by the real‐life needs of the officials of a sports league. At each time slot, a greedy matching heuristic is used to construct a schedule. When an infeasibility is recognized first a single step backtracking is tried to resolve the infeasibility. If unsuccessful, Benders' cuts are generated to guide a large neighborhood search to ensure feasibility and to improve the solution. Realizing the inherent symmetry present in the problem, a large family of cuts are generated and their effectiveness is tested. The resulting approach is able to find better solutions to many instances of this problem. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Polynomial‐time approximation scheme for concurrent open shop scheduling with a fixed number of machines to minimize the total weighted completion time

In this article, we consider the concurrent open shop scheduling problem to minimize the total weighted completion time. When the number of machines is arbitrary, the problem has been shown to be inapproximable within a factor of 4/3 ‐ ε for any ε > 0 if the unique games conjecture is true in the literature. We propose a polynomial time approximation scheme for the problem under the restriction that the number of machines is fixed. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Optimal machine capacity expansions with nested limitations under stochastic demand

This paper studies capacity expansions for a production facility that faces uncertain customer demand for a single product family. The capacity of the facility is modeled in three tiers, as follows. The first tier consists of a set of upper bounds on production that correspond to different resource types (e.g., machine types, categories of manpower, etc.). These upper bounds are augmented in increments of fixed size (e.g., by purchasing machines of standard types). There is a second‐tier resource that constrains the first‐tier bounds (e.g., clean room floor space). The third‐tier resource bounds the availability of the second‐tier resource (e.g., the total floor space enclosed by the building, land, etc.). The second and third‐tier resources are expanded at various times in various amounts. The cost of capacity expansion at each tier has both fixed and proportional elements. The lost sales cost is used as a measure for the level of customer service. The paper presents a polynomial time algorithm (FIFEX) to minimize the total cost by computing optimal expansion times and amounts for all three types of capacity jointly. It accommodates positive lead times for each type. Demand is assumed to be nondecreasing in a “weak” sense. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.