Publications (98)81.6 Total impact

Article: Strongly Polynomial PrimalDual Algorithms for Concave Cost Combinatorial Optimization Problems
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ABSTRACT: We introduce an algorithm design technique for a class of combinatorial optimization problems with concave costs. This technique yields a strongly polynomial primaldual algorithm for a concave cost problem whenever such an algorithm exists for the fixedcharge counterpart of the problem. For many practical concave cost problems, the fixedcharge counterpart is a wellstudied combinatorial optimization problem. Our technique preserves constant factor approximation ratios, as well as ratios that depend only on certain problem parameters, and exact algorithms yield exact algorithms. Using our technique, we obtain a new 1.61approximation algorithm for the concave cost facility location problem. For inventory problems, we obtain a new exact algorithm for the economic lotsizing problem with general concave ordering costs, and a 4approximation algorithm for the joint replenishment problem with general concave individual ordering costs. 
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ABSTRACT: We study the problem of minimizing a nonnegative separable concave function over a compact feasible set. We approximate this problem to within a factor of 1+epsilon by a piecewiselinear minimization problem over the same feasible set. Our main result is that when the feasible set is a polyhedron, the number of resulting pieces is polynomial in the input size of the polyhedron and linear in 1/epsilon. For many practical concave cost problems, the resulting piecewiselinear cost problem can be formulated as a wellstudied discrete optimization problem. As a result, a variety of polynomialtime exact algorithms, approximation algorithms, and polynomialtime heuristics for discrete optimization problems immediately yield fully polynomialtime approximation schemes, approximation algorithms, and polynomialtime heuristics for the corresponding concave cost problems. We illustrate our approach on two problems. For the concave cost multicommodity flow problem, we devise a new heuristic and study its performance using computational experiments. We are able to approximately solve significantly larger test instances than previously possible, and obtain solutions on average within 4.27% of optimality. For the concave cost facility location problem, we obtain a new 1.4991+epsilon approximation algorithm. 
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ABSTRACT: Because of its imbedded network flow structure, the generic network design problem is an attractive candidate for integer programming decomposition. This paper studies the application and acceleration of Benders decomposition for uncapacitated models from this problem class and illustrates the potential flexibility of the Benders solution strategy. In particular, it (i) shows that several lower bounding inequalities from the literature can be derived as Benders cuts; and (ii) introduces new Benders cuts for the network design problem. The paper also reports on computational experience in using Benders decomposition with a dual ascent and variable elimination preprocessing procedure to solve uncapacitated network design problems with up to 90 binary variables and 15 080 continuous variables, or 45 binary variables and 105 600 continuous variables.08/2009: pages 112154; 
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ABSTRACT: We consider two types of hopindexed models for the unitdemand asymmetric Capacitated Vehicle Routing Problem (CVRP): (a) capacitated models guaranteeing that the number of commodities (paths) traversing any given arc does not exceed a specified capacity; and (b) hopconstrained models guaranteeing that any route length (number of nodes) does not exceed a given value. The latter might, in turn, be divided into two classes: (b1) those restricting the length of the path from the depot to any node k, and (b2) those restricting the length of the circuit passing through any node k. Our results indicate that formulations based upon circuit lengths (b2) lead to models with a linear programming relaxation that is tighter than the linear programming relaxation of models based upon path lengths (b1), and that combining features from capacitated models with those of circuit lengths can lead to formulations for the CVRP with a tight linear programming bound. Computational results on a small number of problem instances with up to 41 nodes and 440 edges show that the combined model with capacities and circuit lengths produce average gaps of less than one percent. We also briefly examine the asymmetric travelling salesman problem (ATSP), showing the potential use of the ideas developed for the vehicle routing problem to derive models for the ATSP with a linear programming relaxation bound that is tighter than the linear programming relaxation bound of the standard Dantzig, Fulkerson and Johnson [G. Dantzig, D. Fulkerson, D. Johnson, Solution of largescale travelling salesman problem, Operations Research 2 (1954) 393–410] formulation.Discrete Optimization 05/2008; DOI:10.1016/j.disopt.2007.05.001 · 0.63 Impact Factor 
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ABSTRACT: The function need not be continuous; it can have positive or negative jumps, though we do assume that the function is lower semicontinuous, that is, g a (x a ) lim inf x # a #xa g a (x # a ) for 1 any sequence x # a that approaches x a . Without loss of generality, we also assume, through a simple translation of the costs if necessary, that g a (0) = 0. Such a piecewise linear function can be fully characterized by its segments. On each arc a, each segment s of the function has a nonnegative variable cost, c a (the slope), a nonnegative fixed cost, f a (the intercept), and upper and lower bounds, b a and b a , on the flow of that segment. Since the total flow on each arc can always be bounded from above by either the arc capacity or the total demand flowing through the network, we assume that there is a finite number of segments on each arc a, which we represent by the set S a . We further introduce the following notation: K denotes the set of commodities, N is the VOperations Research 02/2007; 55:146157. DOI:10.1287/opre.1060.0314 · 1.50 Impact Factor 
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ABSTRACT: We study a specialized version of network design problems that arise in telecommunications, transportation, and other industries. The problem, a generalization of the shortest path problem, is defined on an undirected network consisting of a set of arcs on which we can install (load), at a cost, a choice of up to three types of capacitated facilities. Our objective is to determine the configuration of facilities to load on each arc that will satisfy the demand of a single commodity at the lowest possible cost. Our results (i) demonstrate that the singlefacility loading problem and certain “common breakeven point” versions of the twofacility and threefacility loading problems are polynomially solvable as a shortest path problem; (ii) show that versions of the twofacility loading problem are strongly NPhard, but that a shortest path solution provides an asymptotically “good” heuristic; and (iii) characterize the optimal solution (i.e., specify a linear programming formulation with integer solutions) of the common breakeven point versions of the twofacility and threefacility loading problems. In this development, we introduce two new families of facets, give geometric interpretations of our results, and demonstrate the usefulness of partitioning the space of the problem parameters to establish polyhedral integrality properties. Generalizations of our results apply to (i) multicommodity applications and (ii) situations with more than three facilities. © 1993 by John Wiley & Sons, Inc.Networks 10/2006; 23(2):103  121. DOI:10.1002/net.3230230205 · 0.74 Impact Factor 
Article: An intersecting tree model for odddiameterconstrained minimum spanning and Steiner trees.
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ABSTRACT: In a previous paper, Gouveia and Magnanti (2003) found diameterconstrained minimal spanning and Steiner tree problems to be more difficult to solve when the tree diameter D is odd. In this paper, we provide an alternate modeling approach that views problems with odd diameters as the superposition of two problems with even diameters. We show how to tighten the resulting formulation to develop a model with a stronger linear programming relaxation. The linear programming gaps for the tightened model are very small, typically less than 0.5–, and are usually one third to one tenth of the gaps of the best previous model described in Gouveia and Magnanti (2003). Moreover, the new model permits us to solve large Euclidean problem instances that are not solvable by prior approaches.Annals of Operations Research 09/2006; 146:1939. DOI:10.1007/s1047900600490 · 1.10 Impact Factor 
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ABSTRACT: By adding a set of redundant constraints, and by iteratively refining the approximation, we show that a commercial solver is able to routinely solve moderatesize strategic safety stock placement problems to optimality. The speedup arises because the solver automatically generates strong flow cover cuts using the redundant constraints.Operations Research Letters 03/2006; DOI:10.1016/j.orl.2005.04.004 · 0.62 Impact Factor 
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ABSTRACT: The network design problem with connectivity requirements (NDC) models a wide variety of celebrated combinatorial optimization problems including the minimum span ning tree, Steiner tree, and survivable network design problems. We develop strong for mulations for two versions of the edgeconnectivity NDC problem: unitary problems re quiring connected network designs, and nonunitary problems permitting nonconnected networks as solutions. We (i) present a new directed formulation for the unitary NDC problem that is stronger than a natural undirected formulation, (ii) project out several classes of valid inequalities—partition inequalities, oddhole inequalities, and combi natorial design inequalities—that generalize known classes of valid inequalities for the Steiner tree problem to the unitary NDC problem, and (iii) show how to strengthen and direct nonunitary problems. Our results provide a unifying framework for strengthening formulations for NDC problems, and demonstrate the strength and power of ßowbased formulations for net work design problems with connectivity requirements.Networks 03/2005; 45(2):6179. DOI:10.1002/net.20046 · 0.74 Impact Factor 
Article: Solving variational inequality and fixed point problems by line searches and potential optimization.
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ABSTRACT: We introduce a general adaptive line search framework for solving fixed point and variational inequality problems. Our goals are to develop iterative schemes that (i) compute solutions when the underlying map satisfies properties weaker than contractiveness, for example, weaker forms of nonexpansiveness, (ii) are more efficient than the classical methods even when the underlying map is contractive, and (iii) unify and extend several convergence results from the fixed point and variational inequality literatures. To achieve these goals, we introduce and study joint compatibility conditions imposed upon the underlying map and the iterative step sizes at each iteration and consider line searches that optimize certain potential functions. As a special case, we introduce a modified steepest descent method for solving systems of equations that does not require a previous condition from the literature (the square of the Jacobian matrix is positive definite). Since the line searches we propose might be difficult to perform exactly, we also consider inexact line searches.Mathematical Programming 12/2004; 101:435461. DOI:10.1007/s1010700304765 · 1.98 Impact Factor 
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ABSTRACT: In a previous article, using underlying graph theoretical properties, Gouveia and Magnanti (2003) described several network flowbased formulations for diameterconstrained tree problems. Their computational results showed that, even with several enhancements, models for situations when the tree diameter D is odd proved to be more difficult to solve than those when D is even. In this article we provide an alternative modeling approach for the situation when D is odd. The approach views the diameterconstrained minimum spanning tree as being composed of a variant of a directed spanning tree (from an artificial root node) together with two constrained paths, a shortest and a longest path, from the root node to any node in the tree. We also show how to view the feasible set of the linear programming relaxation of the new formulation as the intersection of two integer polyhedra, a socalled triangletree polyhedron and a constrained path polyhedron. This characterization improves upon a model of Gouveia and Magnanti (2003) whose linear programming relaxation feasible set is the intersection of three rather than two integer polyhedra. The linear programming gaps for the tightened model are very small, typically less than 0.5%, and are usually one third to one tenth of the gaps of the best previous model described in Gouveia and Magnanti (2003). Moreover, using the new model, we have been able to solve large Euclidean problem instances that are not solvable by the previous approaches. © 2004 Wiley Periodicals, Inc.Networks 12/2004; 44(4):254265. DOI:10.1002/net.20034 · 0.74 Impact Factor 
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ABSTRACT: The survivable network design (SND) problem seeks a minimumcost robust network configuration that provides a specified number of alternate (edgedisjoint) paths between nodes of the network. For this problem, we present a family of new mixedinteger programming formulations whose associated linear programming relaxations can be tighter than that of the usual cutset formulation. The new formulations, called connectivitysplitting models, strengthen the cutset formulation by splitting the connectivity requirements across critical cutsets (with crossing requirements of at least two) into two separate requirements and strengthening the connectivity constraints across regular cutsets (with crossing requirements of one). As special cases of this broad modeling approach, we obtain three intuitive versions of the model. A connectivitypeeling version peels off the lowest connectivity level, a connectivitydividing version divides the connectivity requirements for all critical cutsets, and an accesscompletion version separates the design decisions for critical cutsets from those for regular cutsets. These stronger formulations motivate several SND combinatorial heuristics and facilitate the analysis of their worstcase performance. Our bounds on the heuristic costs relative to the optimal values of the integer program and the linear programming relaxation of our tighter formulation are stronger than some previously known performance bounds for combinatorial heuristics. © 2003 Wiley Periodicals, Inc.Networks 01/2004; 43(1):10  27. DOI:10.1002/net.10100 · 0.74 Impact Factor 
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ABSTRACT: We study a generic minimization problem with separable nonconvex piecewise linear costs, showing that the linear programming (LP) relaxation of three textbook mixedinteger programming formulations each approximates the cost function by its lower convex envelope. We also show a relationship between this result and classical Lagrangian duality theory.Management Science 09/2003; 49:12681273. DOI:10.1287/mnsc.49.9.1268.16570 · 2.52 Impact Factor 
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ABSTRACT: We develop integer programming formulations and solution methods for addressing operational issues in mergeintransit distribution systems. The models account for various complex problem features, including the integration of inventory and transportation decisions, the dynamic and multimodal components of the application, and the nonconvex piecewise linear structure of the cost functions. To accurately model the cost functions, we introduce disaggregation techniques that allow us to derive a hierarchy of linear programming relaxations. To solve these relaxations, we propose a cuttingplane procedure that combines constraint and variable generation with rounding and branchandbound heuristics. We demonstrate the effectiveness of this approach on a large set of test problems with instances derived from actual data from the computer industry that contain almost 500,000 integer variables.Transportation Science 02/2003; 37(1):122. DOI:10.1287/trsc.37.1.1.12822 · 2.29 Impact Factor 
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ABSTRACT: The DiameterConstrained Minimum Spanning Tree Problem seeks a least cost spanning tree subject to a (diameter) bound imposed on the number of edges in the tree between any node pair. A traditional multicommodity flow model with a commodity for every pair of nodes was unable to solve a 20node and 100edge problem after one week of computation. We formulate the problem as a directed tree from a selected central node or a selected central edge. Our model simultaneously finds a central node or a central edge and uses it as the source for the commodities in a directed multicommodity flow model with hop constraints. The new model has been able to solve the 20node, 100edge instance to optimality after less than four seconds. We also present model enhancements when the diameter bound is odd (these situations are more difficult). We show that the linear programming relaxation of the best formulations discussed in this paper always give an optimal integer solution for two special, polynomiallysolvable cases of the problem. We also examine the Diameter Constrained Minimum Steiner Tree problem. We present computational experience in solving problem instances with up to 100 nodes and 1000 edges. The largest model contains more than 250,000 integer variables and more than 125,000 constraints.Networks 01/2003; DOI:10.1002/net.10069 · 0.74 Impact Factor 
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ABSTRACT: The network restoration problem is a specialized capacitated network design problem requiring the installation of spare capacity to fully restore disrupted network flows if any edge in a telecommunications network fails. We present a new mixedinteger programming formulation for a line restoration version of the problem using a single type of capacitated facility. We examine two different models, for distinct and integrated sparecapacity systems, reflecting technologies used in synchronous transfer mode (STM) and asynchronous transfer mode (ATM) networks. The problem is NPcomplete in the strong sense. We study the problem's polyhedral structure to identify strong valid inequalities that tighten the problem formulation. Our computational results on several real and randomly generated problems show that these inequalities considerably reduce the integrality gap from an average of 10% to an average of under 1%. These results indicate that strong cutting planes combined with branchandbound can provide efficient algorithms for solving a class of realworld problems in the telecommunications industry.Operations Research 08/2002; 50(4):617635. DOI:10.1287/opre.50.4.617.2853 · 1.50 Impact Factor 
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ABSTRACT: We study a scheduling problem with changeover costs and capacity constraints. The problem is NPcomplete, and combinatorial algorithms for solving it have not performed well. We identify a general class of facets that subsumed as special cases some known facets from the literature. We also develop a cuttingplanebased procedure and reformulation for the problem, and we obtain optimal solutions to problem instances with up to 600 integer variables without resorting to branchandbound procedures.Operations Research 08/2002; 50(4). DOI:10.1287/opre.50.4.708.2861 · 1.50 Impact Factor 
Article: Errata for
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ABSTRACT: gically ordered". page 80, line15. "set of path and cycle flow" should be "set of path and cycle flows". page 80, line15. "cycle fow" should be "set of path and cycle flows". page 80, line7. "path and cycle flow" should be "a path and cycle flow". page 83, line 22. "cx = cx 0 + cx " should be "x = x 0 + x,,. page 85, line 1. "used" should be "use". page 85, line 13. "correspond" should be "corresponds". page 86, Exercise 3.9. line 4. "every pairs of elements" should be "every pair of elements". page 86, Exercise 3.9. line 5. "k = 1,..., n" should be "k = 1,..., (nl)". page 86, Exercise 3.9. line 5. "k = 1,..., (n4)" should be "k = 1,..., (nl)". page 90, Exercise 3.34. "the longest path in any depthfirst search tree, no matter which node is selected as the source node" should be "the longest path in some depthfirst search tree". page 92, Figure 3.15. (b) Arrows should be added: 1>4, 2>1, 2>3, 3>1, 3>4, 4>5, 5>1, 5>2. page 92, Exercise 3.51. line 1. "nodej ( i 
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ABSTRACT: An intuitive solutiondoubling argument establishes well known results concerning the worstcase performance of spanning treebased heuristics for the Steiner network problem and the traveling salesman problem. This note shows that the solutiondoubling argument and its implications apply to certain more general Low Connectivity Steiner (LCS) problems that are important in the design of survivable telecommunication networks. We use the doubling strategy to establish worstcase upper bounds on the value of treebased heuristics relative to the optimal value for some versions of the LCS problem, and also provide a tight lower bound based on solutions to matching problems.Operations Research Letters 10/2001; 29(3):99106. DOI:10.1016/S01676377(01)000943 · 0.62 Impact Factor 
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ABSTRACT: To ensure uninterrupted service, telecommunication networks contain excess (spare) capacity for rerouting (restoring) traffic in the event of a link failure. We study the NPhard capacity planning problem of economically installing spare capacity on a network to permit link restoration of steadystate traffic. We present a planning model that incorporates multiple facility types, and develop optimizationbased heuristic solution methods based on solving a linear programming relaxation and minimum cost network flow subproblems. We establish bounds on the performance of the algorithms, and discuss problem instances that nearly achieve these worstcase bounds. In tests on three realworld problems and numerous randomlygenerated problems containing up to 50 nodes and 150 edges, the heuristics provide good solutions (often within 0.5% of optimality) to problems with single facility type, in equivalent or less time than methods from the literature. For multifacility problems, the gap between our heuristic solution values and the linear programming bounds are larger. However, for small graphs, we show that the optimal linear programming value does not provide a tight bound on the optimal integer value, and our heuristic solutions are closer to optimality than implied by the gaps.Annals of Operations Research 01/2001; 106:127154. DOI:10.1023/A:1014509708610 · 1.10 Impact Factor
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7k  Citations  
81.60  Total Impact Points  
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 Operations Research (10)
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Institutions

1974–2009

Massachusetts Institute of Technology
 • Department of Electrical Engineering and Computer Science
 • School of Engineering
 • MIT Sloan School of Management
Cambridge, Massachusetts, United States
