We propose minimum volume ellipsoids (MVE) clustering as an alternate clustering technique to k-means clustering for Gaussian data points and explore its value and practicality. MVE clustering allocates data points into clusters that minimizes the total volumes of each cluster’s covering ellipsoids. Motivations for this approach include its scale-invariance, its ability to handle asymmetric and … Read more
We present a compact linearization for a broad class of bilinear 0-1 mixed-integer problems subject to assignment constraints. We apply the linearization to three classes of problems: quadratic assignment, multiprocessor scheduling with communication delays, and graph partitioning, and show that it yields faster solution times. Citation DEI, Politecnico di Milano, Working paper, April 2005. Article … Read more
Working with an integer bilinear programming formulation of a one-dimensional cutting-stock problem, we develop an ILP-based local-search heuristic. The ILPs holistically integrate the master and subproblem of the usual price driven pattern-generation paradigm, resulting in a unified model that generates new patterns in situ. We work harder to generate new columns, but we are guaranteed … Read more
In this paper we present a restructuring of the computations in Lenstra’s methods for solving mixed integer linear programs. We show that the problem of finding a good branching hyperplane can be formulated on an adjoint lattice of the Kernel lattice of the equality constraints without requiring any dimension reduction. As a consequence the short … Read more
We consider the vehicle routing problem where one can choose among vehicles with different costs and capacities to serve the trips. We develop six different formulations: the first four based on Miller-Tucker-Zemlin constraints and the last two based on flows. We compare the linear programming bounds of these formulations. We derive valid inequalities and lift … Read more
Managing shelf space is critical for retailers to attract customers and to optimize profit. This paper develops a shelf space allocation optimization model that explicitly incorporates essential in-store costs and considers space- and cross-elasticities. The resultant model maximizes a signomial objective function over linear and bilinear constraints in mixed-integer variables. We propose a piecewise linearization … Read more
The Facility Location Model with Risk Pooling (LMRP) extends the uncapacitated fixed charge model to incorporate inventory decisions at the distribution centers (DCs). In this paper, we introduce a capacitated version of the LMRP that handles inventory management at the DCs such that the capacity limitations at the DCs are not exceeded. We consider a … Read more
In this paper we consider a particular class of nonlinear optimization problems involving both continuous and discrete variables. The distinguishing feature of this class of nonlinear mixed optimization problems is that the structure and the number of variables of the problem depend on the values of some discrete variables. In particular we define a general … Read more
We present two capacity choice scenarios for the socially optimal location of facilities with fixed servers, stochastic demand and congestion. Walk-in health clinics, motor vehicle inspection stations, automobile emissions testing stations, and internal service systems are motivating examples of such facilities. The choice of locations for such facilities influences not only distances for users traveling … Read more
We consider the solution of Mixed Integer Nonlinear Programming (MINLP) problems by a parallel implementation of nonlinear branch-and-bound on a computational grid or meta-computer. Computational experience on a set of large MINLPs is reported which indicates that this approach is efficient for the solution of large MINLPs. Citation Numerical Analysis Report NA/200, Department of Mathematics, … Read more