Inherent smoothness of intensity patterns for intensity modulated radiation therapy generated by simultaneous projection algorithms

Categories Biomedical Applications, Convex Optimization Tags , , , ,

The efficient delivery of intensity modulated radiation therapy (IMRT) depends on finding optimized beam intensity patterns that produce dose distributions, which meet given constraints for the tumor as well as any critical organs to be spared. Many optimization algorithms that are used for beamlet-based inverse planning are susceptible to large variations of neighboring intensities. Accurately … Read more

Universal Duality in Conic Convex Optimization

Categories Linear, Cone and Semidefinite Programming Tags , , , ,

Given a primal-dual pair of linear programs, it is well known that if their optimal values are viewed as lying on the extended real line, then the duality gap is zero, unless both problems are infeasible, in which case the optimal values are +infinity and -infinity. In contrast, for optimization problems over nonpolyhedral convex cones, … Read more

On the Globally Concavized Filled Function Method

Categories Global Optimization, Global Optimization Theory Tags , , ,

In this paper we present a new definition on the globally concavized filled function for the continuous global minimization problem, which was modified from that by Ge [3]. A new class of globally concavized filled functions are constructed. These functions contain two easily determinable parameters, which are not dependent on the radius of the basin … Read more

Pointillism via Linear Programming

Categories Airline Optimization, Applications - Science and Engineering, Linear Programming Tags ,

Pointillism is a painting technique in which the painter places dots of paint on the canvas in such a way that they blend together into desired forms when viewed from a distance. In this brief note, we describe how to use linear programming to construct a pointillist portrait. CitationDept. of Mathematics, Oberlin College, Oberlin, OH … Read more

A Simplicial Branch-and-Bound Algorithm for Solving Quadratically Constrained Quadratic Programs

Categories Global Optimization Theory Tags , , ,

We propose a branch-and-bound algorithm for solving nonconvex quadratically-constrained quadratic programs. The algorithm is novel in that branching is done by partitioning the feasible region into the Cartesian product of two-dimensional triangles and rectangles. Explicit formulae for the convex and concave envelopes of bilinear functions over triangles and rectangles are derived and shown to be … Read more

Vehicle routing and staffing for sedan service

Categories Integer Programming, Transportation Tags , , ,

We present the optimization component of a decision support system developed for a sedan service provider. The system assists supervisors and dispatchers in scheduling driver shifts and routing the fleet throughout the day to satisfy customer demands within tight time windows. We periodically take a snapshot of the dynamic data and formulate an integer program, … Read more

Gradient-Controlled, Typical-Distance Clustering for Global Optimization

Categories Global Optimization, Stochastic Approaches Tags , ,

We present a stochastic global optimization method that employs a clustering technique which is based on a typical distance and a gradient test. The method aims to recover all the local minima inside a rectangular domain. A new stopping rule is used. Comparative results on a set of test functions are reported. CitationPreprint, no 4-5/2004 … Read more

Portfolio Investment with the Exact Tax Basis via Nonlinear Programming

Categories Finance and Economics, Stochastic Programming Tags , ,

Computing the optimal portfolio policy of an investor facing capital gains tax is a challenging problem: because the tax to be paid depends on the price at which the security was purchased (the tax basis), the optimal policy is path dependent and the size of the problem grows exponentially with the number of time periods. … Read more

A semidefinite programming based polyhedral cut and price algorithm for the maxcut problem

Categories Branch and Cut Algorithms, Semi-definite Programming Tags , , ,

We investigate solution of the maximum cut problem using a polyhedral cut and price approach. The dual of the well-known SDP relaxation of maxcut is formulated as a semi-infinite linear programming problem, which is solved within an interior point cutting plane algorithm in a dual setting; this constitutes the pricing (column generation) phase of the … Read more

Optimality Measures for Performance Profiles

Categories Nonlinear Optimization Tags ,

We examine the importance of optimality measures when benchmarking a set of solvers, and show that scaling requirements lead to a convergence test for nonlinearly constrained optimization solvers that uses a mixture of absolute and relative error measures. We demonstrate that this convergence test is well behaved at any point where the constraints satisfy the … Read more