Showing papers on "Constraint programming published in 1977"
PARC1
TL;DR: A possible discipline is outlined and expressed in terms of the language Modula, which may be the only practical way to make real-time systems analytically verifiable and ultimately reliable.
Abstract: Programming is divided into three major categories with increasing complexity of reasoning in program validation: sequential programming, multiprogramming, and real-time programming. By adhering to a strict programming discipline and by using a suitable high-level language molded after this discipline, the complexity of reasoning about concurrency and execution time constraints may be drastically reduced. This may be the only practical way to make real-time systems analytically verifiable and ultimately reliable. A possible discipline is outlined and expressed in terms of the language Modula.
202 citations
IBM1
TL;DR: An attempt to provide a powerful mathematical programming language, allowing an easy programming of specific studies on medium-size models such as the recursive use of LP or the build-up of algorithms based on the simplex method is described.
Abstract: First, this paper presents the results of experiments with algorithmic techniques for efficiently solving medium and large scale linear and mixed integer programming problems. The techniques presented here are either original or recent.
142 citations
TL;DR: This session discusses the design and implementation of software for unconstrained optimization, and a proposal for the classification and documentation of test problems in the field of nonlinear programming.
Abstract: History of mathematical programming systems.- Scope of mathematical programming software.- Anatomy of a mathematical programming system.- Elements of numerical linear algebra.- A tutorial on matricial packing.- Pivot selection tactics.- An interactive query system for MPS solution information.- Modeling and solving network problems.- Integer programming codes.- Some considerations in using branch-and bound codes.- Quadratic programming.- Nonlinear programming using a general mathematical programming system.- The design and implementation of software for unconstrained optimization.- The GRG method for nonlinear programming.- Generalized reduced gradient software for linearly and nonlinearly constrained problems.- The ALGOL 60 procedure minifun for solving non-linear optimization problems.- An accelerated conjugate gradient algorithm.- Global optima without convexity.- Computational aspects of geometric programming.- A proposal for the classification and documentation of test problems in the field of nonlinear programming.- Guidelines for reporting computational experiments in mathematical programming.- COAL session summary.- List of participants.
77 citations
TL;DR: It is found that goal programming can be used as a means of generating a range of possible solutions to the planning problem.
Abstract: Goal Programming is similar in structure to linear programming, but offers a more flexible approach to planning problems by allowing a number of goals which are not necessarily compatible to be taken into account, simultaneously. The use of linear programming in farm planning is reviewed briefly. Consideration is given to published evidence of the goals of farmers, and ways in which these goals can be represented. A goal programming model of a 600 acre mixed farm is described and evaluated. Advantages and shortcomings of goal programming in relation to linear programming are considered. It is found that goal programming can be used as a means of generating a range of possible solutions to the planning problem.
62 citations
TL;DR: In this paper, a duality theorem for disjunctive programming has been proved for this class of problems, which generalizes to the class of linear programming problems and generalizes the corresponding result for linear programming.
Abstract: We state a duality theorem for disjunctive programming, which generalizes to this class of problems the corresponding result for linear programming.
26 citations
TL;DR: This note presents a refinement to earlier work that reduces the size of the coefficients in the equivalent constraint and points out advantages as well as computational considerations for solving problems by this method.
Abstract: Integer programming problems with bounded variables can be solved by combining the constraints into an equivalent single constraint. This note presents a refinement to earlier work that reduces the size of the coefficients in the equivalent constraint and points out advantages as well as computational considerations for solving problems by this method.
26 citations
TL;DR: This paper shows that using a recent theory of convex programming, which is free of a constraint qualification assumption, it is possible both to characterize and to calculate the optimal solutions of the convex lexicographic problem.
Abstract: Mathematical programming formulation of the convex lexicographic multi-criteria problems typically lacks a constraint qualification. Therefore the classical Kuhn-tucker theory fails to characterize their optimal solutions. Furthermore, numerical methods for solving the lexicographic problems are virtually nonexistent. This paper shows that using a recent theory of convex programming, which is free of a constraint qualification assumption, it is possible both to characterize and to calculate the optimal solutions of the convex lexicographic problem.
15 citations
Proceedings Article•
01 Jan 1977
13 citations