Many classes of mathematical programming problems can be formulated as a linear program with a parametric objective function. Gass and Saaty developed in the early 1950's a parametric programming procedure for sol...
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Many classes of mathematical programming problems can be formulated as a linear program with a parametric objective function. Gass and Saaty developed in the early 1950's a parametric programming procedure for solving the latter problem. This procedure is relevant to solution strategies for many problem types but is underutilized, often because the relationship of the procedure to the relevant problem class is not recognized. In this paper five recent applications of the parametric programming procedure are presented.
Reliable dissemination of bulk data is one of the important problems in sensor networks. For example, programming or upgrading the software in sensors at run-time requires reliable dissemination of a new program acros...
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Reliable dissemination of bulk data is one of the important problems in sensor networks. For example, programming or upgrading the software in sensors at run-time requires reliable dissemination of a new program across the network. In this paper, we present Infuse, a time division multiple access (TDMA) based reliable data dissemination protocol. Infuse takes two input parameters: i. the choice of the recovery algorithm (from one of two presented in this paper) to deal with unexpected channel errors (e.g., message corruption, varying signal strength), and ii. whether a sensor should listen only to a subset of its neighbors to reduce the amount of active radio time. Based on these parameters, we obtain four possible versions of Infuse. We compare the performance of these versions to assist a designer in selecting the appropriate version based on the network characteristics. Furthermore, we demonstrate Infuse in the context of network programming.
In this paper we are concerned with a special class of bicriterion path problems. For the considered class of bicriterion problems at least one of the objectives is type MAXMIN. For the other one, besides an objective...
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In this paper we are concerned with a special class of bicriterion path problems. For the considered class of bicriterion problems at least one of the objectives is type MAXMIN. For the other one, besides an objective type MAXMIN also a MINSUM and a MINRATIO type objective are considered. Two algorithms are presented for the considered class of bicriterion path problems. The first one only determines the minimal complete set of nondominated paths and the second one determines the entire set of non-dominated paths. Both algorithms can be used for any type of bicriterion path problems, since one of the objectives is type MAXMIN and an algorithm exists to determine the best path for the other objective. Computational statistics for the three types of considered bicriterion path problems are also presented. [ABSTRACT FROM AUTHOR]
In 1965 Helmut Lerchs and Ingo Grossmann presented to the mining community an algorithm to find the optimum design for an open pit mine. In their words, "the objective is to design the contour of a pit so as to m...
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In 1965 Helmut Lerchs and Ingo Grossmann presented to the mining community an algorithm to find the optimum design for an open pit mine. In their words, "the objective is to design the contour of a pit so as to maximize the difference between total mine value of the ore extracted and the total extraction cost of ore and waste". They modeled the problem in graph theoretic terms and showed that an optimal solution of the ultimate pit problem is equivalent to finding the maximum closure of their graph based model. In this paper, we develop a network flow algorithm based on the dual to solve the same problem. We show how this algorithm is closely related to Lerchs and Grossmann's and how the steps in their algorithm can be viewed in mathematical programming terms. This analysis adds insight to the algorithm of Lerchs and Grossmann and shows where it can be made more efficient. As in the case Lerchs and Grossmann, our algorithm allows us to use very efficient data structures based on graphs that represent the data and constraints. (C) 1998 Elsevier Science B.V.
The partial sum criterion with parameter p adds up the p largest weights in the solution, giving the criterion value to be minimized. For p = 1 the criterion is the bottleneck or minmax criterion. For the minmax Stein...
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The partial sum criterion with parameter p adds up the p largest weights in the solution, giving the criterion value to be minimized. For p = 1 the criterion is the bottleneck or minmax criterion. For the minmax Steiner tree problem in graphs we describe an O(\E\) algorithm with E being the set of edges in the problem graph. The algorithm unifies two existing algorithms, one of them solves the bottleneck shortest path problem and the other the bottleneck spanning tree problem. For the shortest path problem we consider the criterion for arbitrary values of p, defining it for solutions with less than p edges as the total sum. For an undirected graph with n nodes we present an O(n(3)) algorithm to determine, simultaneously, partial sum shortest paths between all pairs of nodes and for all values of the parameter p. For the 2-sum shortest path problem and one pair of nodes we give an O(\E\ + n log n) algorithm. By exploiting this algorithm we obtain the same complexity for the 2-sum Steiner tree problem in graphs. Furthermore, we discuss the complexity of related problems and alternative partial sum criteria.
作者：
Gendron, BUniv Montreal
Ctr Rech Transports Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada
We show by a counterexample that the dual-ascent procedure proposed by Herrmann, Ioannou, Minis and Proth in a 1996 issue of the European Journal of Operational Research is incorrect in the sense that it does not gene...
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We show by a counterexample that the dual-ascent procedure proposed by Herrmann, Ioannou, Minis and Proth in a 1996 issue of the European Journal of Operational Research is incorrect in the sense that it does not generate a valid lower bound to the optimal value of fixed-charge capacitated network design problems. We provide a correct dual-ascent procedure based on the same ideas and we give an interpretation of it in terms of a simple Lagrangean relaxation. Although correct, this procedure is not effective, as in general, it provides a less tighter bound than the linear programming relaxation. (C) 2002 Elsevier Science B.V. All rights reserved.
Sun's announcement of the programming language Java more than anything popularized the notion of mobile code, that is, programs traveling on a heterogeneous network and automatically executing upon arrival at the ...
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Sun's announcement of the programming language Java more than anything popularized the notion of mobile code, that is, programs traveling on a heterogeneous network and automatically executing upon arrival at the destination. We describe several classes of mobile code and extract their common characteristics, where security proves to be one of the major concerns. With these characteristics as reference points, we examine six representative languages proposed for mobile code. The conclusion of this study leads to our recommendations for future work, illustrated by examples of ongoing research.
In this work we focus on partial information models for the well-known shortest path problem, where we consider multiple instances of values for the parameters that determine the cost of each are. This allows coping w...
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In this work we focus on partial information models for the well-known shortest path problem, where we consider multiple instances of values for the parameters that determine the cost of each are. This allows coping with the uncertainty about the future, the imprecision of data, the arbitrariness of some options, the evolving values of the decision makers (DMs) and/or the multiplicity of DMs (in group decision making). This paper proves some results and presents detailed algorithms to identify the set of non dominated paths, a concept from decision theory under partial information. We first address problems with a finite set of instances. then problems with a general (eventually not discrete) set of instances and finally we study a particular case of the latter, which complies with a condition that may hold in some situations. To deal with these partial information problems we propose a new use for existing multicriteria algorithms based on the ranking of shortest paths. (C) 2000 Elsevier Science B.V. All rights reserved.
A particular problem concerning the efficient production of printed circuit boards in the electronics industry is addressed. It concerns the location of feeder bins which contain parts to be inserted in the boards. We...
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A particular problem concerning the efficient production of printed circuit boards in the electronics industry is addressed. It concerns the location of feeder bins which contain parts to be inserted in the boards. We address the question of identifying the optimal bin locations in order to determine the best insertion sequence of the parts. The location problem is formulated as a number of one-facility location models. The sequencing problem is formulated as a traveling salesman problem. Techniques are presented for these problems which accomodate a variety of distance norms and take into account the possibility of only certain feasible regions for the location of the bins.
An approximation of an explicitly or implicitly given convex curve in the plane is given by two piecewise linear 'outer' and 'inner' curves. To compute these, three rules for choosing the supporting po...
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An approximation of an explicitly or implicitly given convex curve in the plane is given by two piecewise linear 'outer' and 'inner' curves. To compute these, three rules for choosing the supporting points are proposed and it is shown for two of them that the projective distance between inner and outer approximation decreases quadratically with the number of supporting points. This method is applied to approximate the efficient point curve of the Bicriterial Minimum Cost Flow Problem, which is a piecewise linear convex curve that may have an exponential number of breakpoints in the worst case. [ABSTRACT FROM AUTHOR]
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