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The article presents comments on the management science paper "On Sequencing n Jobs on One Machine to Minimize the Number of Late Jobs," by William L. Maxwell. The paper focused on an integer programming formulation of a one-machine job shop problem. The author contends that Maxwell made in error in proving the validity of an optimal algorithm by applying cutting plane constraints to the problem. The author explains that the problem cannot be solved through traditional cutting plane procedures. The author provides a mathematical model in an attempt to correct the proof.

The paper considers a class of optimization problems. The problems are linear programming problems: maximize ex subject to Ax = b with the additional constraint that x must also be an extreme point of a second convex polyhedron Dx = d. X ≥ 0. A cutting-plane algorithm for solving such problems is presented. Two numerical examples are also included. [ABSTRACT FROM AUTHOR]

The article presents an algorithm for solving a linear integer programming problem and describes the theoretical foundations for a new approach to integer programming. According to the authors, the approach may be described as an extension of the methods using enumeration, but by using a new, more powerful approach based on population statistics. The optimal solution to the integer programming problem in this paper is viewed as one of selecting the optimal function among a certain class of functions which map elements of one set into another. With this method in mind, the authors intend to view the different problems by characterizing the statistical structure of the associated finite class of maps.

The usefulness of integer programming as a tool of capital budgeting hinges on the development of an efficient solution technique. An algorithm based on partial enumeration has been developed by E. L. Lawler and M. D. Bell for solving integer linear programs with 0-1 decision variables; however their algorithm is not general enough to deal with all problems in which the objective function is quadratic. This paper extends Lawler and Bell's method so that it can be generally applied to integer quadratic programs. The new algorithm is illustrated by examples from capital budgeting. [ABSTRACT FROM AUTHOR]

This paper attempts to present the major methods, successful or interesting uses, and computational experience relating to integer or discrete programming problems. Included are descriptions of general algorithms for solving linear programs in integers, as well as some special purpose algorithms for use on highly structured problems. This reflects a belief, on the author's part, that various clever methods of enumeration and other specialized approaches are the most efficacious means existent by which to obtain solutions to practical problems. A serious try at gathering computational experience has been made—but facts are difficult to uncover. The paper is written with intent to enable readers to read selected sections without having to read the whole. [ABSTRACT FROM AUTHOR]

This paper presents new types of cutting-plane algorithms for integer-constrained optimization problems. The underlying idea of the method of enumerative cuts is to make use of an enumeration procedure in order to construct cutting planes that can be made arbitrarily deep. In recent publications, BALLAS and YOUNG have established in somewhat different contexts that valid cutting planes can be generated from the intersection of (basic) rays with adequately constructed hyperspheres. This paper introduces a family of polyhedra to replace the sphere; these polyhedra are not tangential to the hypersphere and produce cutting planes with particular characteristics that are discussed. Constructive procedures are sketched for generating step-by-step cutting planes that become deeper and deeper at every step, until the deepest cut is obtained. This construction often relies on a partial enumeration scheme of the set of integer solutions. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for the solution of the knapsack problem. The method involves searching the nodes of a tree along a single branch at a time. The algorithm eliminates the computational drawbacks inherent in the usual branch and bound schemes. [ABSTRACT FROM AUTHOR]

It has been established that integer programs with integral, recursive constraint matrices have integral extreme points for integral, nonnegative requirement vectors. In this paper, it is first shown that the assignment problem can be transformed to such a program, but with upper bounds on some variables. This equivalent program leads to additional results for solving the assignment problem. Algorithms are then delineated to transform matching, covering and travelling salesman problems to equivalent recursive programs of the aforementioned type, but with bounds on some variables. These results are extended to programs with special structure in their constraint matrices. [ABSTRACT FROM AUTHOR]

This paper connects some of the recent developments in concave and integer programming. In particular, it points out parallels between the work of HOANG TUI and R. D. YOUNG. From these methods, a finite algorithm for solving a special class of 0–1 integer programs is developed. Our approach contrasts with an earlier extension of Tui's method due to M. RAGHAVACHARI and general ‘intersection’ or ‘convexity’ cut approaches. [ABSTRACT FROM AUTHOR]

The convex hull of the feasible integer points to a given integer program is a convex polytope I. The feasible set obtained by relaxing the integrality requirements is another convex polytope L. Cutting-plane algorithms essentially try to remove part of L--I. Hence the more complicated the relationship between L and I, the more difficult (in some sense) the integer program. This paper shows one such complexity: specifically, we construct a series of programs such that I has arbitrarily many faces even though L is a triangle. We also indicate the existence of a large class of problems that exhibit the same behavior. [ABSTRACT FROM AUTHOR]

This paper reports on a new computer code (called "LIP1") for solving integer programming problems, which will be distributed for general use through SHARE. LIP1 was written as an experimental program for the purpose of reexamining and further testing the efficiency of GOMORY's original cutting-plane technique. Many trial problems have now been solved with this code. Of particular interest, however, are 25 test problems that have been solved with other integer programming codes (all these other codes incorporate the method of Gomory's more recent all-integer algorithm). The basis for comparing the performance of the various codes is the number of iterations required to solve each problem. For these 25 test problems LIP1 appears generally as efficient as the other codes tested. Moreover, on the more difficult problems LIP1 generally performed better than the other codes. We conclude that Gomory's original cutting-plane method merits further investigation and development as an efficient computational technique. [ABSTRACT FROM AUTHOR]

Following a line of approach recently applied to the 0-1 integer programming problem with some success by EGON BALAS, the algorithm of this paper is based upon an underlying tree-search structure upon which a series of tests is superimposed to exclude large portions of the tree of all possible 0-1 solutions from examination. In our method, the specific design of the enumeration and tests, supplemented by the use of a special type of constraint called a `surrogate constraint,' results in an algorithm that appears to be quite efficient in relation to other algorithms currently available for solving the 0-1 integer programming problem. Early indications of efficiency must, however, be regarded as suggestive rather than conclusive, due to the limited range and size of problems so far examined. Following the analytical development of the method, three example problems are solved in detail with the Multiphase-Dual Algorithm to illustrate various aspects of its application. An extension of the algorithm to the general integer pro- gramming problem in bounded variables is briefly sketched in a concluding section. [ABSTRACT FROM AUTHOR]

The methods of R. E. Gomory for the iterative solution of the mixed-integer linear programming problem are extended directly to the case where some or all of the variables are nonuniformly discrete, i.e., they are restricted to assume values from certain specified sets of unequally-spaced constants. The algorithm presented is shown to converge in a finite number of steps for a discrete-valued objective function. [ABSTRACT FROM AUTHOR]

A unifying framework is developed to facilitate the understanding of most known computational approaches to integer programming. A number of currently operational algorithms are related to this framework, and prospects for future progress are assessed. [ABSTRACT FROM AUTHOR]

The usefulness of group theoretic methods in solving integer programming (IP) problems is extended by procedures for controlling the size of the groups. The main procedure given shows how an optimal linear programming basis can be altered to reduce the magnitude of its determinant thereby reducing the size of the group induced by the basis. An adaption of Benders' mixed IP algorithm is given which uses these methods. Some limited computational experience is given. [ABSTRACT FROM AUTHOR]

A theory of equivalent integer programs is developed that shows that every all-integer integer programming problem is equivalent to infinitely many other integer programming problems. The equivalence is such that the solution to any one problem in the equivalence class determines the solution to every other problem in the class. Procedures to construct certain canonical problems in each equivalence class are described. The relationship of this theory to computational algorithms is discussed. [ABSTRACT FROM AUTHOR]

A method is presented for test construction and scoring which utilizes the knapsack model of mathematical programming. The method applies to examinations of the type in which a choice exists in the number of questions the examinee is required to answer. The method has been utilized with respect to a mathematics examination and computer generated results of this test are provided. [ABSTRACT FROM AUTHOR]